Artikel
2023
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Mohr, S.; Ehret, U.; Kunz, M.; Ludwig, P.; Caldas-Alvarez, A.; Daniell, J. E.; Ehmele, F.; Feldmann, H.; Franca, M. J.; Gattke, C.; Hundhausen, M.; Knippertz, P.; Küpfer, K.; Mühr, B.; Pinto, J. G.; Quinting, J.; Schäfer, A. M.; Scheibel, M.; Seidel, F.; Wisotzky, C. (2023). A multi-disciplinary analysis of the exceptional flood event of July 2021 in central Europe. Part 1: Event description and analysis. Natural hazards and earth system sciences, 23 (2), 525–551. doi:10.5194/nhess-23-525-2023
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Schäfer, A. M.; Daniell, J. E.; Mühr, B.; Skapski, J.-U.; Mohr, S.; Kunz, M. (2023). CEDIM Forensic Disaster Analysis Group (FDA): Kahramanmaraş & Elbistan Erdbeben Türkei. doi:10.5445/IR/1000155770
2022
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Andersen, H.; Cermak, J.; Zipfel, L.; Myers, T. A. (2022). Attribution of Observed Recent Decrease in Low Clouds Over the Northeastern Pacific to Cloud‐Controlling Factors. Geophysical research letters, 49 (3), e2021GL096498. doi:10.1029/2021GL096498
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Bertels, M.; Jutzi, B.; Ulrich, M. (2022). Automatic Real-Time Pose Estimation of Machinery from Images. Sensors, 22 (7), 2627. doi:10.3390/s22072627
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Bluhm, R.; Polonik, P.; Hemes, K. S.; Sanford, L. C.; Benz, S. A.; Levy, M. C.; Ricke, K. L.; Burney, J. A. (2022). Disparate air pollution reductions during California’s COVID-19 economic shutdown. Nature Sustainability, 5 (6), 509–517. doi:10.1038/s41893-022-00856-1
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Boé, J.; Mass, A.; Deman, J. (2022). A simple hybrid statistical–dynamical downscaling method for emulating regional climate models over Western Europe. Evaluation, application, and role of added value?. Climate Dynamics. doi:10.1007/s00382-022-06552-2
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Boldt, M.; Thiele, A.; Schulz, K. (2022). Training data generation for machine learning using GPR images. Proceedings Volume 12268, Earth Resources and Environmental Remote Sensing/GIS Applications XIII, Ed.: K. Schulz, 122680F, SPIE. doi:10.1117/12.2635714
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Bradley, P. E.; Jahn, M. W. (2022). On the Behaviour of p-Adic Scaled Space Filling Curve Indices for High-Dimensional Data. The computer journal, 65 (2), 310–330. doi:10.1093/comjnl/bxaa036
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Christensen, M. W.; Gettelman, A.; Cermak, J.; Dagan, G.; Diamond, M.; Douglas, A.; Feingold, G.; Glassmeier, F.; Goren, T.; Grosvenor, D. P.; Gryspeerdt, E.; Kahn, R.; Li, Z.; Ma, P.-L.; Malavelle, F.; McCoy, I. L.; McCoy, D. T.; McFarquhar, G.; Mülmenstädt, J.; Pal, S.; Possner, A.; Povey, A.; Quaas, J.; Rosenfeld, D.; Schmidt, A.; Schrödner, R.; Sorooshian, A.; Stier, P.; Toll, V.; Watson-Parris, D.; Wood, R.; Yang, M.; Yuan, T. (2022). Opportunistic experiments to constrain aerosol effective radiative forcing. Atmospheric chemistry and physics, 22 (1), 641–674. doi:10.5194/acp-22-641-2022
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Döring, A.; Vogelbacher, M.; Schneider, O.; Müller, J.; Hinz, S.; Matthes, J. (2022). Ratio-based features for bridge damage detection based on displacement influence line and curvature influence line. Bridge Safety, Maintenance, Management, Life-Cycle, Resilience and Sustainability, CRC Press.
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Dörr, N.; Schenk, A.; Hinz, S. (2022). On the Relevance of Temporary Persistent Scatterers for Long-Term PS-InSAR Monitoring. EUSAR 2022 ; 14th European Conference on Synthetic Aperture Radar, 541–546, VDE Verlag.
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Dörr, N.; Schenk, A.; Hinz, S. (2022). Systematic Analysis of Initial Settlement of new Constructions in the Mekong Delta by Coherence Change Detection of Temporary Persistent Scatterers. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, 17-22 July 2022, 1111–1114, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS46834.2022.9883381
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Dörr, N.; Schenk, A.; Hinz, S. (2022). Fully Integrated Temporary Persistent Scatterer Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 60, Art no. 4412815. doi:10.1109/TGRS.2022.3200155
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Evers, M.; Thiele, A.; Hammer, H.; Hinz, S. (2022). The Filling Process of an Embankment Dam Monitored with PSI. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 1640–1643, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS46834.2022.9883950
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Fersch, B.; Kamm, B.; Shehaj, E.; Wagner, A.; Yuan, P.; Möller, G.; Schenk, A.; Geiger, A.; Hinz, S.; Kutterer, H.; Kunstmann, H. (2022). A comprehensive high resolution data collection for tropospheric water vapor assessment for the Upper Rhine Graben, Germany. doi:10.1594/PANGAEA.936447
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Fersch, B.; Wagner, A.; Kamm, B.; Shehaj, E.; Schenk, A.; Yuan, P.; Geiger, A.; Moeller, G.; Heck, B.; Hinz, S.; Kutterer, H.; Kunstmann, H. (2022). Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region. Earth System Science Data, 14 (12), 5287–5307. doi:10.5194/essd-14-5287-2022
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Florath, J.; Keller, S. (2022). Supervised Machine Learning Approaches on Multispectral Remote Sensing Data for a Combined Detection of Fire and Burned Area. Remote sensing, 14 (3), Art.-Nr.: 657. doi:10.3390/rs14030657
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Florath, J.; Keller, S.; Abarca-del-Rio, R.; Hinz, S.; Staub, G.; Weinmann, M. (2022). Glacier Monitoring Based on Multi-Spectral and Multi-Temporal Satellite Data: A Case Study for Classification with Respect to Different Snow and Ice Types. Remote sensing, 14 (4), Article no: 845. doi:10.3390/rs14040845
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Franke, S.; Jansen, D.; Binder, T.; Paden, J. D.; Dörr, N.; Gerber, T. A.; Miller, H.; Dahl-Jensen, D.; Helm, V.; Steinhage, D.; Weikusat, I.; Wilhelms, F.; Eisen, O. (2022). Airborne ultra-wideband radar sounding over the shear margins and along flow lines at the onset region of the Northeast Greenland Ice Stream. Earth system science data, 14 (2), 763–779. doi:10.5194/essd-14-763-2022
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Fuchs, J.; Andersen, H.; Cermak, J.; Pauli, E.; Roebeling, R. (2022). High-resolution satellite-based cloud detection for the analysis of land surface effects on boundary layer clouds. Atmospheric Measurement Techniques, 15 (14), 4257–4270. doi:10.5194/amt-15-4257-2022
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Haitz, D.; Hübner, P.; Ulrich, M.; Landgraf, S.; Jutzi, B. (2022). Semantic segmentation with small training datasets: A case study for corrosion detection on the surface of industrial objects. Forum Bildverarbeitung 2022. Ed.: T. Längle; M. Heizmann, 73–85, KIT Scientific Publishing.
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Haitz, D.; Jutzi, B.; Hübner, P.; Ulrich, M. (2022). Corrosion detection for industrial objects: from multi-sensor system to 5D feature space. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B1-2022, 143–150. doi:10.5194/isprs-archives-XLIII-B1-2022-143-2022
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Hammer, H.; Kuny, S.; Schmitz, S.; Thielea, A. (2022). Training a CNN with Simulated Data for ATR – Lessons Learned. EUSAR 2022; 14th European Conference on Synthetic Aperture Radar, 1–6, Institute of Electrical and Electronics Engineers (IEEE).
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Heizmann, M.; Braun, A.; Glitzner, M.; Günther, M.; Hasna, G.; Klüver, C.; Krooß, J.; Marquardt, E.; Overdick, M.; Ulrich, M. (2022). Implementing machine learning: chances and challenges. Automatisierungstechnik, 70 (1), 90–101. doi:10.1515/auto-2021-0149
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Hübner, P.; Wursthorn, S.; Weinmann, M. (2022). Normal classification of 3D occupancy grids for voxel-based indoor reconstruction from point clouds. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-4-2022, 121–128. doi:10.5194/isprs-annals-V-4-2022-121-2022
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Jahani, B.; Andersen, H.; Calbó, J.; González, J.-A.; Cermak, J. (2022). Longwave radiative effect of the cloud–aerosol transition zone based on CERES observations. Atmospheric chemistry and physics, 22 (2), 1483–1494. doi:10.5194/acp-22-1483-2022
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Jahn, M. W.; Bradley, P. E. (2022). Topological Access Methods for Spatial and Spatiotemporal Data. ISPRS International Journal of Geo-Information, 11 (10), 533. doi:10.3390/ijgi11100533
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Jahn, M. W.; Bradley, P. E. (2022). A Robustness Study for the Extraction of Watertight Volumetric Models from Boundary Representation Data. ISPRS International Journal of Geo-Information, 11 (4), Artk.Nr.: 224. doi:10.3390/ijgi11040224
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Kühnlein, L.; Keller, S. (2022). Evaluation of Transformers and Convolutional Neural Networks for High-Dimensional Hyperspectral Soil Texture Classification. 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WHISPERS56178.2022.9955087
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Landgraf, S.; Kühnlein, L.; Hillemann, M.; Hoyer, M.; Keller, S.; Ulrich, M. (2022). Evaluation of self-supervised learning approaches for semantic segmentation of industrial burner flames. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2022, 601–607. doi:10.5194/isprs-archives-XLIII-B2-2022-601-2022
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Li, J.; Weinmann, M.; Sun, X.; Diao, W.; Feng, Y.; Hinz, S.; Fu, K. (2022). VD-LAB: A view-decoupled network with local-global aggregation bridge for airborne laser scanning point cloud classification. ISPRS Journal of Photogrammetry and Remote Sensing, 186, 19–33. doi:10.1016/j.isprsjprs.2022.01.012
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Ludwig, P.; Ehmele, F.; Franca, M. J.; Mohr, S.; Caldas-Alvarez, A.; Daniell, J. E.; Ehret, U.; Feldmann, H.; Hundhausen, M.; Knippertz, P.; Küpfer, K.; Kunz, M.; Mühr, B.; Pinto, J. G.; Quinting, J.; Schäfer, A. M.; Seidel, F.; Wisotzky, C. (2022). A multi-disciplinary analysis of the exceptional flood event of July 2021 in central Europe. Part 2: Historical context and relation to climate change. Natural hazards and earth system sciences discussions. doi:10.5194/nhess-2022-225
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Mao, Y.; Chen, K.; Diao, W.; Sun, X.; Lu, X.; Fu, K.; Weinmann, M. (2022). Beyond single receptive field: A receptive field fusion-and-stratification network for airborne laser scanning point cloud classification. ISPRS Journal of Photogrammetry and Remote Sensing, 188, 45–61. doi:10.1016/j.isprsjprs.2022.03.019
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Mayer, M.; Przybilla, M.; Kamm, B.; Krüger, S.; Rabold, J. (2022). Training of Ethical Competencies in Bsc Degree Programs – a Digital, Multi-Perspective, and Student-Centered Approach. XXVII FIG Congress: Volunteering for the future - Geospatial excellence for a better living.
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Michel, C.; Keller, S. (2022). Determining and Investigating the Variability of Bridges’ Natural Frequencies with Ground-Based Radar. Applied Sciences, 12 (11), Artk.Nr.: 5354. doi:10.3390/app12115354
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Palka, J.; Lenz, A.; Middelmann, W.; Weinmann, M. (2022). Evaluation of the NEON dataset for the automatic detection of treetops and delineation of tree crowns in American and German mixed forests. Proceedings Volume 12268, Earth Resources and Environmental Remote Sensing/GIS Applications XIII, Art.-Nr.: 1226807, SPIE. doi:10.1117/12.2643747
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Pauli, E.; Cermak, J.; Andersen, H. (2022). A satellite‐based climatology of fog and low stratus formation and dissipation times in central Europe. Quarterly Journal of the Royal Meteorological Society, 148 (744), 1439–1454. doi:10.1002/qj.4272
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Pauli, E.; Cermak, J.; Teuling, A. J. (2022). Enhanced nighttime fog and low stratus occurrence over the Landes forest, France. Geophysical research letters, 49 (5), e2021GL097058. doi:10.1029/2021GL097058
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Rebmeister, M.; Auer, S.; Schenk, A.; Hinz, S. (2022). Geocoding of ground-based SAR data for infrastructure objects using the Maximum A Posteriori estimation and ray-tracing. ISPRS Journal of Photogrammetry and Remote Sensing, 189, 110–127. doi:10.1016/j.isprsjprs.2022.04.030
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Schäfer, A.; Daniell, J. E.; Skapski, J.-U.; Mohr, S. (2022). CEDIM Forensic Disaster Analysis Group (FDA) "Volcano & Tsunami Hunga Tonga" Report No. 1. doi:10.5445/IR/1000142014
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Schill, F.; Michel, C.; Firus, A. (2022). Contactless Deformation Monitoring of Bridges with Spatio-Temporal Resolution: Profile Scanning and Microwave Interferometry. Sensors, 22 (23), Art.-Nr.: 9562. doi:10.3390/s22239562
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Schmitz, S.; Thiele, A.; Hammer, H.; Hinz, S. (2022). Impact of highly varying incidence angle on the feature space of polsar images. EUSAR 2022; 14th European Conference on Synthetic Aperture Radar, 360–365, Institute of Electrical and Electronics Engineers (IEEE).
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Steger, C.; Ulrich, M. (2022). A Multi-view Camera Model for Line-Scan Cameras with Telecentric Lenses. Journal of Mathematical Imaging and Vision, 64, 105–130. doi:10.1007/s10851-021-01055-x
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Sun, X.; Wang, P.; Yan, Z.; Xu, F.; Wang, R.; Diao, W.; Chen, J.; Li, J.; Feng, Y.; Xu, T.; Weinmann, M.; Hinz, S.; Wang, C.; Fu, K. (2022). FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 184, 116–130. doi:10.1016/j.isprsjprs.2021.12.004
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Wursthorn, K.; Hillemann, M.; Ulrich, M. (2022). Comparison of uncertainty quantification methods for CNN-based regression. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2022, 721–728. doi:10.5194/isprs-archives-XLIII-B2-2022-721-2022
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Yang, Y.; Cermak, J.; Yang, K.; Pauli, E.; Chen, Y. (2022). Land Use and Land Cover Influence on Sentinel-2 Aerosol Optical Depth below City Scales over Beijing. Remote Sensing, 14 (18), Art.-Nr.: 4677. doi:10.3390/rs14184677
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Zipfel, L.; Andersen, H.; Cermak, J. (2022). Machine-Learning Based Analysis of Liquid Water Path Adjustments to Aerosol Perturbations in Marine Boundary Layer Clouds Using Satellite Observations. Atmosphere, 13 (4), Art.-Nr.: 586. doi:10.3390/atmos13040586
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Zube, A.; Kleiser, D.; Albrecht, A.; Woock, P.; Emter, T.; Ruf, B.; Tchouchenkov, I.; Buller, A.; Wagner, B.; Baatar, G.; Petereit, J. (2022). Autonomously mapping shallow water environments under and above the water surface [Autonome Kartierung von Flachwasserumgebungen unter und über der Wasseroberflache]. at - Automatisierungstechnik, 70 (5), 482–495. doi:10.1515/auto-2021-0145
2021
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Andersen, H.; Cermak, J.; Stirnberg, R.; Fuchs, J.; Kim, M.; Pauli, E. (2021). Assessment of COVID-19 effects on satellite-observed aerosol loading over China with machine learning. Tellus / B, 73 (1), 1–13. doi:10.1080/16000889.2021.1971925
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Arnold, M.; Hoyer, M.; Keller, S. (2021). Convolutional Neural Networks for Detecting Bridge Crossing Events with Ground-Based Interferometric Radar Data. ISPRS annals, V-1-2021, 31–38. doi:10.5194/isprs-annals-V-1-2021-31-2021
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Benz, S. A.; Davis, S. J.; Burney, J. A. (2021). Drivers and projections of global surface temperature anomalies at the local scale. Environmental Research Letters, 16 (6), Article no: 064093. doi:10.1088/1748-9326/ac0661
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Benz, S. A.; Burney, J. A. (2021). Widespread Race and Class Disparities in Surface Urban Heat Extremes Across the United States. Earth’s Future, 9 (7), e2021EF002016. doi:10.1029/2021EF002016
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Bulatov, D.; Stütz, D.; Hacker, J.; Weinmann, M. (2021). Classification of airborne 3D point clouds regarding separation of vegetation in complex environments. Applied Optics, 60 (22), F6-F20. doi:10.1364/AO.422973
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Döring, A.; Waibel, P.; Matthes, J.; Scherer, O.; Keller, H. B.; Keller, S.; Müller, J.; Schneider, O. (2021). Ratio-based features for data-driven bridge monitoring and damage detection. Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations. Ed.: H. Yokota, 2532–2541, CRC Press. doi:10.1201/9780429279119-346
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Dörr, N.; Schenk, A.; Hinz, S. (2021). Analysis of Heterogeneous PS-InSAR Derived Subsidence Rates Using Categorized GIS Objects - A Case Study in the Mekong Delta. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 11-16 July 2021, 2655–2658, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS47720.2021.9553297
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Dubois, C.; Jutzi, B.; Olijslagers, M.; Pathe, C.; Schmullius, C.; Stelmaszczuk-Górska, M. A.; Vandenbroucke, D.; Weinmann, M. (2021). Knowledge and skills related to active optical sensors in the body of knowledge for earth observation and geoinformation (EO4GEO BOK). ISPRS annals, V-5-2021, 9–16. doi:10.5194/isprs-annals-V-5-2021-9-2021
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Erdnüß, B. (2021). A review of the one-parameter division undistortion model. Volume V-1-2021, 2021 | XXIV ISPRS Congress Imaging today, foreseeing tomorrow, Commission I: 2021 edition, 5-9 July 2021. Ed.: N. Paparoditis, 89–96, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-annals-V-1-2021-89-2021
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Evers, M.; Thiele, A.; Hammer, H.; Cadario, E.; Schulz, K.; Hinz, S. (2021). Concept to analyze the displacement time series of individual persistent scatterers. XXIV ISPRS Congress (2021 edition). Ed.: N. Paparoditis, 147–154, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLIII-B3-2021-147-2021
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Florath, J.; Keller, S.; Staub, G.; Weinmann, M. (2021). Optical Remote Sensing for Glacier Monitoring with Respect to Different Snow and Ice Types: A Case Study for the Southern Patagonian Icefield. 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 24–26 March 2021, Article no: 33, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WHISPERS52202.2021.9484055
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Guth, J.; Keller, S.; Hinz, S.; Winter, S. (2021). Towards detecting, characterizing and rating of road class errors in crowd-sourced road network databases. Journal of spatial information science, 22, 31. doi:10.5311/JOSIS.2021.22.677
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Hammer, H.; Lorenz, F.; Cadario, E.; Kuny, S.; Thiele, A. (2021). Enhancement of coherence images for coherent change detection. 13th European Conference on Synthetic Aperture Radar, EUSAR 2021: Online ; 29 March 2021 through 1 April 2021, 881–886, Institute of Electrical and Electronics Engineers (IEEE).
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Hammer, H.; Kuny, S.; Thiele, A. (2021). Enhancing coherence images for coherent change detection: An example on vehicle tracks in airborne sar images. Remote Sensing, 13 (24), 5010. doi:10.3390/rs13245010
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Hermann, M.; Ruf, B.; Weinmann, M. (2021). Real-Time Dense 3D Reconstruction from Monocular Video Data Captured by Low-Cost UAVS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2021, 361–368. doi:10.5194/isprs-archives-XLIII-B2-2021-361-2021
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Hermann, M.; Pollok, T.; Brommer, D.; Zahn, D. (2021). IVS3D: An Open Source Framework for Intelligent Video Sampling and Preprocessing to Facilitate 3D Reconstruction.
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Hermann, M.; Pollok, T.; Brommer, D.; Zahn, D. (2021). IVS3D: An Open Source Framework for Intelligent Video Sampling and Preprocessing to Facilitate 3D Reconstruction. Advances in Visual Computing: 16th International Symposium, ISVC 2021, Virtual Event, October 4-6, 2021, Proceedings, Part I. Ed.: G. Bebis, 441–454, Springer Verlag. doi:10.1007/978-3-030-90439-5_35
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Hinz, S.; Feitosa, R. Q.; Weinmann, M.; Jutzi, B. (2021). PREFACE: TECHNICAL COMMISSION I. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B1-2021, 7. doi:10.5194/isprs-archives-XLIII-B1-2021-7-2021
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Hinz, S.; Feitosa, R. Q.; Weinmann, M.; Jutzi, B. (2021). Preface: Technical Commission I. ISPRS annals, V-1-2021, 7. doi:10.5194/isprs-annals-V-1-2021-7-2021
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Hübner, P.; Weinmann, M.; Wursthorn, S.; Hinz, S. (2021). Pose Normalization of Indoor Mapping Datasets Partially Compliant with the Manhattan World Assumption. Remote sensing, 13 (23), 4765. doi:10.3390/rs13234765
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Hübner, P.; Weinmann, M.; Wursthorn, S.; Hinz, S. (2021). Automatic voxel-based 3D indoor reconstruction and room partitioning from triangle meshes. ISPRS journal of photogrammetry and remote sensing, 181, 254–278. doi:10.1016/j.isprsjprs.2021.07.002
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Jahn, M. W.; Bradley, P. E. (2021). Computing watertight volumetric models from boundary representations to ensure consistent topological operations. ISPRS annals, VIII-4/W2-2021, 21–28. doi:10.5194/isprs-annals-VIII-4-W2-2021-21-2021
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Jijón-Palma, M. E.; Kern, J.; Amisse, C.; Centeno, J. A. S. (2021). Improving stacked-autoencoders with 1D convolutional-nets for hyperspectral image land-cover classification. Journal of applied remote sensing, 15 (2), Artikel-Nr.: 026506. doi:10.1117/1.JRS.15.026506
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Kattenborn, T.; Leitloff, J.; Schiefer, F.; Hinz, S. (2021). Review on Convolutional Neural Networks (CNN) in vegetation remote sensing. ISPRS journal of photogrammetry and remote sensing, 173, 24–49. doi:10.1016/j.isprsjprs.2020.12.010
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Krüger, S.; Mayer, M. (2021). Nachwuchs-Forum "Wie entsteht Berufsethik? - Ein empirischer Antwortversuch". Mitteilungen und Veröffentlichungen aus den Themenbereichen Geodäsie, Geoinformation und Landmanagement, (2), 23–26.
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Kuny, S.; Hammer, H.; Schulz, K. (2021). On the classifier performance for simulation based debris detection in sar imagery. Volume XLIII-B1-2021, XXIV ISPRS Congress Imaging today, foreseeing tomorrow, Commission I: 2021 edition, 5–9 July 2021. Ed.: N. Paparoditis, 45–50, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLIII-B1-2021-45-2021
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Leeuw, G. de; A, R. van der; Bai, J.; Xue, Y.; Varotsos, C.; Li, Z.; Fan, C.; Chen, X.; Christodoulakis, I.; Ding, J.; Hou, X.; Kouremadas, G.; Li, D.; Wang, J.; Zara, M.; Zhang, K.; Zhang, Y. (2021). Air Quality over China. Remote sensing, 13 (17), Art.-Nr.: 3542. doi:10.3390/rs13173542
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Li, J.; Weinmann, M.; Sun, X.; Diao, W.; Feng, Y.; Fu, K. (2021). Random Topology and Random Multiscale Mapping: An Automated Design of Multiscale and Lightweight Neural Network for Remote-Sensing Image Recognition. IEEE Transactions on Geoscience and Remote Sensing, 60, Art.Nr. 5610917. doi:10.1109/TGRS.2021.3102988
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Ma, J.; Zhou, J.; Liu, S.; Göttsche, F.-M.; Zhang, X.; Wang, S.; Li, M. (2021). Continuous evaluation of the spatial representativeness of land surface temperature validation sites. Remote sensing of environment, 265, Article no: 112669. doi:10.1016/j.rse.2021.112669
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Maier, P.; Keller, S.; Hinz, S. (2021). Deep Learning with WASI Simulation Data for Estimating Chlorophyll a Concentration of Inland Water Bodies. Remote sensing, 13 (4), 718. doi:10.3390/rs13040718
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Michel, C.; Keller, S. (2021). Introducing a non-invasive monitoring approach for bridge infrastructure with ground-based interferometric radar. 13th European Conference on Synthetic Aperture Radar, EUSAR 2021: Online ; 29 March 2021 through 1 April 2021, 1073–1077, Institute of Electrical and Electronics Engineers (IEEE).
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Michel, C.; Keller, S. (2021). Advancing Ground-Based Radar Processing for Bridge Infrastructure Monitoring. Sensors, 21 (6), 2172. doi:10.3390/s21062172
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Pauli, E.; Cermak, J.; Andersen, H. (2021, Dezember 20). Satellite-based fog and low stratus cloud formation and dissipation times data set. doi:10.5445/IR/1000141293
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Rabold, J.; Heublein, M.; Mayer, M. (2021). Beteiligung von Studierenden bei der Weiterentwicklung des Lehr-Lernsystems. Die Hochschullehre, (6), 520–528. doi:10.3278/HSL2041W
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Rebmeister, M.; Schenk, A.; Bradley, P. E.; Dörr, N.; Hinz, S. (2021). OCLeaS – A tomographic PSI Algorithm using Orthogonal Matching Pursuit and Complex Least Squares. Procedia computer science, 181, 220–230. doi:10.1016/j.procs.2021.01.143
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Ruf, B.; Mohrs, J.; Weinmann, M.; Hinz, S.; Beyerer, J. (2021). ReS²tAC—UAV-borne real-time SGM stereo optimized for embedded ARM and CUDA devices. Sensors, 21 (11), Article: 3938. doi:10.3390/s21113938
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Schenkel, F.; Hinz, S.; Middelmann, W. (2021). Style transfer-based domain adaptation for vegetation segmentation with optical imagery. Applied optics, 60 (22), F109-F117. doi:10.1364/AO.423910
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Schmitz, S.; Weidner, U.; Hammer, H.; Thiele, A. (2021). Evaluating uniform manifold approximation and projection for dimension reduction and visualization of polinsar features. Volume V-1-2021, 2021 | XXIV ISPRS Congress Imaging today, foreseeing tomorrow, Commission I: 2021 edition, 5-9 July 2021. Ed.: N. Paparoditis, 39–46, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-annals-V-1-2021-39-2021
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Schmitz, S.; Wortmeyer, E.; Thiele, A.; Dirks, H.; Wurpts, A. (2021). Detection of Mussel Beds Using Airborne Polarimetric SAR Data. IGARSS 2021 – 2021 IEEE International Geoscience and Remote Sensing Symposium: Proceedings ; 12–16 July 2021, Virtual Symposium, Brussels, Belgium, 7501–7504, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS47720.2021.9553437
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Schneider, B.; Wortmeyer, E.; Schmitz, S.; Thiele, A.; Havel, P.; Dirks, H. (2021). Evaluating different water-land-boundary approximations to improve sar-derived digital elevation models. L. F. Y. M. Y. H. S. F. R. Q. W. M. J. B. Paparoditis N. Mallet C. (Hrsg.), Volume XLIII-B1-2021, XXIV ISPRS Congress Imaging today, foreseeing tomorrow, Commission I: 2021 edition, 5–9 July 2021. Ed.: N. Paparoditis, 51–56, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLIII-B1-2021-51-2021
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Sefrin, O.; Riese, F. M.; Keller, S. (2021). Deep Learning for Land Cover Change Detection. Remote sensing, 13 (1), Article no: 78. doi:10.3390/rs13010078
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Steger, C.; Ulrich, M. (2021). A Camera Model for Line-Scan Cameras with Telecentric Lenses. International journal of computer vision, 129, 80–99. doi:10.1007/s11263-020-01358-3
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Stirnberg, R.; Cermak, J.; Kotthaus, S.; Haeffelin, M.; Andersen, H.; Fuchs, J.; Kim, M.; Petit, J.-E.; Favez, O. (2021). Meteorology-driven variability of air pollution (PM₁) revealed with explainable machine learning. Atmospheric chemistry and physics, 21 (5), 3919–3948. doi:10.5194/acp-21-3919-2021
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Sun, X.; Wang, P.; Yan, Z.; Diao, W.; Lu, X.; Yang, Z.; Zhang, Y.; Xiang, D.; Yan, C.; Guo, J.; Dang, B.; Wei, W.; Xu, F.; Wang, C.; Hansch, R.; Weinmann, M.; Yokoya, N.; Fu, K. (2021). Automated High-resolution Earth Observation Image Interpretation: Outcome of the 2020 Gaofen Challenge. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14. doi:10.1109/JSTARS.2021.3106941
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Sun, X.; Wang, P.; Yan, Z.; Xu, F.; Wang, R.; Diao, W.; Chen, J.; Li, J.; Feng, Y.; Xu, T.; Weinmann, M.; Hinz, S.; Wang, C.; Fu, K. (2021). FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery. doi:10.48550/arXiv.2103.05569
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Ulrich, M.; Hillemann, M. (2021). Generic Hand–Eye Calibration of Uncertain Robots. IEEE International Conference on Robotics and Automation (ICRA), 30 May-5 June 2021, 11060–11066, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICRA48506.2021.9560823
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Vey, S.; Al-Halbouni, D.; Haghighi, M. H.; Alshawaf, F.; Vüllers, J.; Güntner, A.; Dick, G.; Ramatschi, M.; Teatini, P.; Wickert, J.; Weber, M. (2021). Delayed subsidence of the Dead Sea shore due to hydro-meteorological changes. Scientific Reports, 11 (1), 13518. doi:10.1038/s41598-021-91949-y
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Weinmann, M.; Wursthorn, S.; Weinmann, M.; Hübner, P. (2021). Efficient 3D Mapping and Modelling of Indoor Scenes with the Microsoft HoloLens: A Survey. Journal of photogrammetry, remote sensing and geoinformation science, 89, 319–333. doi:10.1007/s41064-021-00163-y
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Wit, K. de; Lexmond, B. R.; Stouthamer, E.; Neussner, O.; Dörr, N.; Schenk, A.; Minderhoud, P. S. J. (2021). Identifying Causes of Urban Differential Subsidence in the Vietnamese Mekong Delta by Combining InSAR and Field Observations. Remote sensing, 13 (2), Art.-Nr. 189. doi:10.3390/rs13020189
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Yang, Y.; Chen, Y.; Yang, K.; Cermak, J.; Chen, Y. (2021). High-resolution aerosol retrieval over urban areas using sentinel-2 data. Atmospheric research, 264, Art.-Nr.: 105829. doi:10.1016/j.atmosres.2021.105829
2020
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Andersen, H.; Cermak, J.; Fuchs, J.; Knippertz, P.; Gaetani, M.; Quinting, J.; Sippel, S.; Vogt, R. (2020). Synoptic-scale controls of fog and low-cloud variability in the Namib Desert. Atmospheric chemistry and physics, 20 (6), 3415–3438. doi:10.5194/acp-20-3415-2020
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Arnold, M.; Keller, S. (2020). Detection and classification of bridge crossing Events with ground-based interferometric radar data and machine learning approaches. ISPRS annals, V-1-2020, 109–116. doi:10.5194/isprs-annals-V-1-2020-109-2020
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Bradley, P. E. (2020). Generalised Diffusion on Moduli Spaces of p-Adic Mumford Curves. P-adic numbers, ultrametric analysis, and applications, 12 (2), 73–89. doi:10.1134/S2070046620020016
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Breunig, M.; Bradley, P. E.; Jahn, M.; Kuper, P.; Mazroob, N.; Rösch, N.; Al-Doori, M.; Stefanakis, E.; Jadidi, M. (2020). Geospatial Data Management Research: Progress and Future Directions. ISPRS International Journal of Geo-Information, 9 (2), 95. doi:10.3390/ijgi9020095
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Bulatov, D.; Stütz, D.; Lucks, L.; Weinmann, M. (2020). Superpoints in RANSAC planes: A new approach for ground surface extraction exemplified on point classification and context-aware reconstruction. Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP. Ed.: K. Bouatouch, 25–37, SciTePress. doi:10.5220/0008895600250037
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Bulatov, D.; Burkard, E.; Ilehag, R.; Kottler, B.; Helmholz, P. (2020). From multi-sensor aerial data to thermal and infrared simulation of semantic 3D models: Towards identification of urban heat islands. Infrared physics & technology, 105, Art. Nr.: 103233. doi:10.1016/j.infrared.2020.103233
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Erdnuess, B. (2020). Proper synchronization of geospatial metadata in motion imagery and its evaluation. Geospatial Informatics X 2020; None; United States; 27 April 2020 through 8 May 2020, Art. Nr.: 113980C, SPIE. doi:10.1117/12.2558696
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Erdnüß, B.; Müller, T. (2020). Leistungsstarke und effiziente Bildinterpolation. Forum Bildverarbeitung 2020. Ed.: T. Längle ; M. Heizmann, 253–265, KIT Scientific Publishing.
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Evers, M.; Kyriou, A.; Thiele, A.; Hammer, H.; Nikolakopoulos, K.; Schulz, K. (2020). How to set up a dam monitoring system with PSInSAR and GPS. Earth Resources and Environmental Remote Sensing/GIS Applications XI. Ed.: K. Schulz, Art.-Nr.: 115340L, SPIE. doi:10.1117/12.2573880
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Evers, M.; Hammer, H.; Thiele, A.; Schulz, K. (2020). Strategies for PS processing of large sentinel-1 datasets. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLIII-B1-2020, 2020, XXIV ISPRS Congress (2020 edition). Ed.: N. Paparoditis, 99–106, ISPRS. doi:10.5194/isprs-archives-XLIII-B1-2020-99-2020
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Franke, S.; Jansen, D.; Binder, T.; Dörr, N.; Helm, V.; Paden, J.; Steinhage, D.; Eisen, O. (2020). Bed topography and subglacial landforms in the onset region of the Northeast Greenland Ice Stream. Annals of Glaciology, 61 (81), 143–153. doi:10.1017/aog.2020.12
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Guth, J.; Wursthorn, S.; Keller, S. (2020). Multi-Parameter Estimation of Average Speed in Road Networks Using Fuzzy Control. ISPRS International Journal of Geo-Information, 9 (1), Article No.55. doi:10.3390/ijgi9010055
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Heizmann, M.; Braun, A.; Hüttel, M.; Klüver, C.; Marquardt, E.; Overdick, M.; Ulrich, M. (2020). Artificial intelligence with neural networks in optical measurement and inspection systems. Automatisierungstechnik, 68 (6), 477–487. doi:10.1515/auto-2020-0006
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Hermann, M.; Ruf, B.; Weinmann, M.; Hinz, S. (2020). Self-Supervised Learning for Monocular Depth Estimation from Aerial Imagery. ISPRS annals, V-2-2020, 357–364. doi:10.5194/isprs-annals-V-2-2020-357-2020
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Heublein, M.; Bradley, P. E.; Hinz, S. (2020). Observing geometry effects on a Global Navigation Satellite System (GNSS)-based water vapor tomography solved by least squares and by compressive sensing. Annales geophysicae, 38 (1), 179–189. doi:10.5194/angeo-38-179-2020
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Hinz, S.; Feitosa, R. Q.; Weinmann, M.; Jutzi, B. (2020). PREFACE: TECHNICAL COMMISSION I. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 43 (B1), 7. doi:10.5194/isprs-archives-XLIII-B1-2020-7-2020
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Hinz, S.; Feitosa, R. Q.; Weinmann, M.; Jutzi, B. (2020). Preface: Technical Commission I. ISPRS annals, 5 (1), 7. doi:10.5194/isprs-annals-V-1-2020-7-2020
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Hübner, P.; Clintworth, K.; Liu, Q.; Weinmann, M.; Wursthorn, S. (2020). Evaluation of HoloLens Tracking and Depth Sensing for Indoor Mapping Applications. Sensors, 20 (4), 1021. doi:10.3390/s20041021
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Hübner, P.; Weinmann, M.; Wursthorn, S. (2020). Voxel-Based Indoor Reconstruction from HoloLens Triangle Meshes. ISPRS annals, V-4-2020, 79–86. doi:10.5194/isprs-annals-V-4-2020-79-2020
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Ilehag, R.; Leitloff, J.; Weinmann, M.; Schenk, A. (2020). Urban Material Classification Using Spectral and Textural Features Retrieved from Autoencoders. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume V-1-2020, 2020, XXIV ISPRS Congress (2020 edition). Ed.: N. Paparoditis, 25–32, ISPRS. doi:10.5194/isprs-annals-V-1-2020-25-2020
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Keller, S.; Gabriel, R.; Guth, J. (2020). Machine Learning Framework for the Estimation of Average Speed in Rural Road Networks with OpenStreetMap Data. ISPRS International Journal of Geo-Information, 9 (11), Art.-Nr.: 638. doi:10.3390/ijgi9110638
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Keller, S.; Michel, C.; Schneider, O.; Müller, J.; Arnold, M.; Döring, A.; Hoyer, M.; Hinz, S.; Keller, H. B. (2020). Überwachung von Brückeninfrastrukturen : Neuer Ansatz von konventionellen und berührungslosen Sensoren. Brückenbau, (3), 22–29.
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Keller, S.; Riese, F. M.; Allroggen, N.; Jackisch, C. (2020, Mai). HydReSGeo: Field experiment dataset of surface-sub-surface infiltration dynamics acquired by hydrological, remote sensing, and geophysical measurement techniques. doi:10.5880/fidgeo.2020.015
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Kim, M.; Kim, H.-C.; Im, J.; Lee, S.; Han, H. (2020). Object-based landfast sea ice detection over West Antarctica using time series ALOS PALSAR data. Remote sensing of environment, 242, 111782. doi:10.1016/j.rse.2020.111782
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Kim, M.; Cermak, J.; Andersen, H.; Fuchs, J.; Stirnberg, R. (2020). A New Satellite-Based Retrieval of Low-Cloud Liquid-Water Path Using Machine Learning and Meteosat SEVIRI Data. Remote sensing, 12 (21), Article: 3475. doi:10.3390/rs12213475
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Kubisch, S.; Guth, J.; Keller, S.; Bull, M. T.; Keller, L.; Braun, A. C. (2020). The contribution of tsunami evacuation analysis to evacuation planning in Chile: Applying a multi-perspective research design. International journal of disaster risk reduction, 45, Article No.101462. doi:10.1016/j.ijdrr.2019.101462
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Maier, P. M.; Keller, S. (2020). SpecWa: Spectral remote sensing data and chlorophyll a values of inland waters. doi:10.5880/fidgeo.2020.036
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Mayer, M.; Rabold, J.; Raible, B.; Muhler, M.; Krüger, S. (2020). Forum für Lehre 2019 am KIT: Geodäsie und Geoinformatik : Ein interdisziplinäres Berufsfeld mit hoher gesellschaftlicher Relevanz. Mitteilungen und Veröffentlichungen aus den Themenbereichen Geodäsie, Geoinformation und Landmanagement, (1), 62–67.
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Pauli, E.; Andersen, H.; Bendix, J.; Cermak, J.; Egli, S. (2020). Determinants of fog and low stratus occurrence in continental central Europe – a quantitative satellite-based evaluation. Journal of hydrology, 591, Art.-Nr.: 125451. doi:10.1016/j.jhydrol.2020.125451
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Riese, F. M. (2020, März). Hyperspectral Processing Scripts for the HydReSGeo Dataset 1.0.0. doi:10.5281/zenodo.3706418
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Riese, F. M.; Keller, S.; Hinz, S. (2020). Supervised and Semi-Supervised Self-Organizing Maps for Regression and Classification Focusing on Hyperspectral Data. Remote sensing, 12 (1), Art. Nr.: 7. doi:10.3390/rs12010007
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Riese, F. M.; Schroers, S.; Wienhöfer, J.; Keller, S. (2020, April 9). Aerial Peruvian Andes Campaign (ALPACA) Dataset 2019. doi:10.5445/IR/1000118082
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Schmitt, A.; Wendleder, A.; Kleynmans, R.; Hell, M.; Roth, A.; Hinz, S. (2020). Multi-source and multi-temporal image fusion on hypercomplex bases. Remote sensing, 12 (6), 943. doi:10.3390/rs12060943
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Schmitz, S.; Weinmann, M.; Thiele, A. (2020). Incorporating interferometric coherence into lulc classification of airborne polsar-images using fully convolutional networks. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLIII-B1-2020, 2020, XXIV ISPRS Congress (2020 edition). Ed.: N. Paparoditis, 115–122, ISPRS. doi:10.5194/isprs-archives-XLIII-B1-2020-115-2020
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Sefrin, O.; Riese, F. M.; Keller, S. (2020). Code for Deep Learning for Land Cover Change Detection 1.0.1. doi:10.5281/zenodo.4289079
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Shatnawi, N.; Weidner, U.; Hinz, S. (2020). Monitoring Urban Expansion as a Result of Refugee Fluxes in North Jordan Using Remote Sensing Techniques. Journal of urban planning and development, 146 (3), Art.-Nr.: 04020026. doi:10.1061/(ASCE)UP.1943-5444.0000584
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Stirnberg, R.; Cermak, J.; Fuchs, J.; Andersen, H. (2020). Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning. Journal of geophysical research / D, 125 (4), Art.e2019JD031380. doi:10.1029/2019JD031380
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Wagner, P.; Riese, F. M.; Keller, S. (2020). CAOS Sentinel-2 Pipeline in Python. doi:10.5281/zenodo.3879622
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Weinmann, M.; Jäger, M. A.; Wursthorn, S.; Jutzi, B.; Weinmann, M.; Hübner, P. (2020). 3D Indoor Mapping with the Microsoft HoloLens: Qualitative and Quantitative Evaluation by Means of Geometric Features. ISPRS annals, V-1-2020, 165–172. doi:10.5194/isprs-annals-V-1-2020-165-2020
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Westerhuis, S.; Fuhrer, O.; Cermak, J.; Eugster, W. (2020). Identifying the key challenges for fog and low stratus forecasting in complex terrain. Quarterly journal of the Royal Meteorological Society, 146 (732), 3347–3367. doi:10.1002/qj.3849
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Woollam, J.; Rietbrock, A.; Leitloff, J.; Hinz, S. (2020). HEX: Hyperbolic Event eXtractor, a Seismic Phase Associator for Highly Active Seismic Regions. Seismological research letters, 91 (5), 2769–2778. doi:10.1785/0220200037
2019
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Adler, B.; Babić, K.; Kalthoff, N.; Lohou, F.; Lothon, M.; Dione, C.; Pedruzo-Bagazgoitia, X.; Andersen, H. (2019). Nocturnal low-level clouds in the atmospheric boundary layer over southern West Africa: an observation-based analysis of conditions and processes. Atmospheric chemistry and physics, 19 (1), 663–681. doi:10.5194/acp-19-663-2019
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Andersen, H.; Cermak, J.; Solodovnik, I.; Lelli, L.; Vogt, R. (2019). Spatiotemporal dynamics of fog and low clouds in the Namib unveiled with ground- and space-based observations. Atmospheric chemistry and physics, 19 (7), 4383–4392. doi:10.5194/acp-19-4383-2019
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Babić, K.; Adler, B.; Kalthoff, N.; Andersen, H.; Dione, C.; Lohou, F.; Lothon, M.; Pedruzo-Bagazgoitia, X. (2019). The observed diurnal cycle of low-level stratus clouds over southern West Africa: a case study. Atmospheric chemistry and physics, 19 (2), 1281–1299. doi:10.5194/acp-19-1281-2019
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Benz, S.; Park, H.; Li, J.; Crawl, D.; Block, J.; Nguyen, M.; Altintas, I. (2019). Understanding a Rapidly Expanding Refugee Camp Using Convolutional Neural Networks and Satellite Imagery. 15th International Conference on eScience (eScience), 243–251, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eScience.2019.00034
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Boldt, M.; Thiele, A.; Schulz, K.; Meyer, F. J.; Hinz, S. (2019). Practical approach for synthetic aperture radar change analysis in urban environments. Journal of applied remote sensing, 13 (03), Article: 0345281. doi:10.1117/1.JRS.13.034528
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Bradley, P. E. (2019). Methodology for the sequence analysis of building stocks. Building research and information, 47 (2), 141–155. doi:10.1080/09613218.2018.1380343
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Bradley, P. E. (2019). On the Logistic Behaviour of the Topological Ultrametricity of Data. Journal of classification, 36 (2), 266–276.
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Bradley, P. E.; Behnisch, M. (2019). Heavy-tailed distributions for building stock data. Environment and planning / B, 46 (7), 1281–1296. doi:10.1177/2399808318794499
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Erdnüß, B. (2019). Calibration and synchronization of geospatial metadata for aerial sensor systems. Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII. Ed.: I. Kadar, Art.-Nr.: 1101819, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2518905
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Fuchs, S.; Hilgert, S.; Sotiri, K.; Wagner, A.; Ishikawa, M.; Kern, J.; Jirka, S.; Klassen, I.; Krumm, J.; Malewski, C.; Rohr, H.; Pakzad, K. (2019). Sustainable management of reservoirs - defining minimum data needs and model complexity. GRoW- Water as a Global Resource, Status Seminar 2019, Frankfurt. MuDak-WRM: Multidisciplinary data acquisition as key for a globally applicable water resource management, 12–15, adelphi.
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Giovanella, A.; Bradley, P. E.; Wursthorn, S. (2019). Evaluation of Topological Consistency in CityGML. ISPRS International Journal of Geo-Information, 8 (6), Article: 278. doi:10.3390/ijgi8060278
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Guth, J.; Wursthorn, S.; Braun, A. C.; Keller, S. (2019). Development of a generic concept to analyze the accessibility of emergency facilities in critical road infrastructure for disaster scenarios: exemplary application for the 2017 wildfires in Chile and Portugal. Natural hazards, 97 (3), 979–999. doi:10.1007/s11069-019-03672-7
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Hillemann, M.; Meidow, J.; Jutzi, B. (2019). Impact of different trajectories on extrinsic self-calibration for vehicle-based mobile laser scanning systems. The international archives of photogrammetry, remote sensing and spatial information sciences, XLII-2/W16, 119–125. doi:10.5194/isprs-archives-XLII-2-W16-119-2019
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Hillemann, M.; Weinmann, M.; Mueller, M. S.; Jutzi, B. (2019). Automatic Extrinsic Self-Calibration of Mobile Mapping Systems Based on Geometric 3D Features. Remote sensing, 11 (16), Article: 1955. doi:10.3390/rs11161955
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Hübner, P.; Landgraf, S.; Weinmann, M.; Wursthorn, S. (2019). Evaluation of the Microsoft HoloLens for the Mapping of Indoor Building Environments. 39. Wissenschaftlich-Technische Jahrestagung der DGPF - Dreiländertagung OVG – DGPF – SGPF - Photogrammetrie - Fernerkundung - Geoinformation, Wien, 20 - 22. Februar 2019. Ed. T. B. Kersten, 44–53, Deutsche Gesellschaft für Photogrammetrie.
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Ilehag, R.; Schenk, A.; Huang, Y.; Hinz, S. (2019). KLUM: An urban VNIR and SWIR spectral library consisting of building materials. Remote sensing, 11 (18), Article: 2149. doi:10.3390/rs11182149
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JET Contributors; Eriksson, J.; Hellesen, C.; Binda, F.; Cecconello, M.; Conroy, S.; Ericsson, G.; Giacomelli, L.; Gorini, G.; Hjalmarsson, A.; Kiptily, V. G.; Mantsinen, M.; Nocente, M.; Sahlberg, A.; Salewski, M.; Sharapov, S.; Tardocchi, M. (2019). Measuring fast ions in fusion plasmas with neutron diagnostics at JET. Plasma physics and controlled fusion, 61 (1), Art. Nr.: 014027. doi:10.1088/1361-6587/aad8a6
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JET Contributors; Fitzgerald, M.; Buchanan, J.; Sharapov, S. E.; Kiptily, V. G.; Sertoli, M.; Szepesi, G.; Boom, J.; Akers, R. J.; King, D.; Abduallev, S.; Abhangi, M.; Abreu, P.; Afzal, M.; Aggarwal, K. M.; Ahlgren, T.; Ahn, J. H.; Aho-Mantila, L.; Aiba, N.; Airila, M.; Albanese, R.; Aldred, V.; Alegre, D.; Alessi, E.; Aleynikov, P.; Alfier, A.; Alkseev, A.; Allinson, M.; Alper, B.; Alves, E.; Ambrosino, G.; Ambrosino, R.; Amicucci, L.; Amosov, V.; Sunden, E. A.; Angelone, M.; Anghel, M.; Angioni, C.; Appel, L.; Appelbee, C.; Arena, P.; Ariola, M.; Arnichand, H.; Arshad, S.; Ash, A.; Ashikawa, N.; Aslanyan, V.; Asunta, O.; Auriemma, F.; Austin, Y.; Avotina, L.; Axton, M. D.; Ayres, C.; Bacharis, M.; Baciero, A.; Baiao, D.; Bailey, S.; Baker, A.; Balboa, I.; Balden, M.; Balshaw, N.; Bament, R.; Banks, J. W.; Baranov, Y. F.; Barnard, M. A.; Barnes, D.; Barnes, M.; Barnsley, R.; Wiechec, A. B.; Orte, L. B.; Baruzzo, M.; Basiuk, V.; Bassan, M.; Bastow, R.; Batista, A.; Batistoni, P.; Baughan, R.; Bauvir, B.; Baylor, L.; Bazylev, B.; Beal, J.; Beaumont, P. S.; Beckers, M.; Beckett, B.; Becoulet, A.; Bekris, N.; Beldishevski, M.; Bell, K.; Belli, F.; Bellinger, M.; Belonohy, E.; Ben Ayed, N.; Benterman, N. A.; Bergsaker, H.; Bernardo, J.; Bernert, M.; Berry, M.; Bertalot, L.; Besliu, C.; Beurskens, M.; Bieg, B.; Bielecki, J.; Biewer, T.; Bigi, M.; Bilkova, P.; Binda, F.; Bisoffi, A.; Bizarro, J. P. S.; Bjorkas, C.; Blackburn, J.; Blackman, K.; Blackman, T. R.; Blanchard, P.; Blatchford, P.; Bobkov, V.; Boboc, A.; Bodnar, G.; Bogar, O.; Bolshakova, I.; Bolzonella, T.; Bonanomi, N.; Bonelli, F.; Boom, J.; Booth, J.; Borba, D.; Borodin, D.; Borodkina, I.; Botrugno, A.; Bottereau, C.; Boulting, P.; Bourdelle, C.; Bowden, M.; Bower, C.; Bowman, C.; Boyce, T.; Boyd, C.; Boyer, H. J.; Bradshaw, J. M. A.; Braic, V.; Bravanec, R.; Breizman, B.; Bremond, S.; Brennan, P. D.; Breton, S.; Brett, A.; Brezinsek, S.; Bright, M. D. J.; Brix, M.; Broeckx, W.; Brombin, M.; Broslawski, A.; Brown, D. P. D.; Brown, M.; Bruno, E.; Bucalossi, J.; Buch, J.; Buchanan, J.; Buckley, M. A.; Budny, R.; Bufferand, H.; Bulman, M.; Bulmer, N.; Bunting, P.; Buratti, P.; Burckhart, A.; Buscarino, A.; Busse, A.; Butler, N. K.; Bykov, I.; Byrne, J.; Cahyna, P.; Calabro, G.; Calvo, I.; Camenen, Y.; Camp, P.; Campling, D. C.; Cane, J.; Cannas, B.; Capel, A. J.; Card, P. J.; Cardinali, A.; Carman, P.; Carr, M.; Carralero, D.; Carraro, L.; Carvalho, B. B.; Carvalho, I.; Carvalho, P.; Casson, F. J.; Castaldo, C.; Catarino, N.; Caumont, J.; Causa, F.; Cavazzana, R.; Cave-Ayland, K.; Cavinato, M.; Cecconello, M.; Ceccuzzi, S.; Cecil, E.; Cenedese, A.; Cesario, R.; Challis, C. D.; Chandler, M.; Chandra, D.; Chang, C. S.; Chankin, A.; Chapman, I. T.; Chapman, S. C.; Chernyshova, M.; Chitarin, G.; Ciraolo, G.; Ciric, D.; Citrin, J.; Clairet, F.; Clark, E.; Clark, M.; Clarkson, R.; Clatworthy, D.; Clements, C.; Cleverly, M.; Coad, J. P.; Coates, P. A.; Cobalt, A.; Coccorese, V.; Cocilovo, V.; Coda, S.; Coelho, R.; Coenen, J. W.; Coffey, I.; Colas, L.; Collins, S.; Conka, D.; Conroy, S.; Conway, N.; Coombs, D.; Cooper, D.; Cooper, S. R.; Corradino, C.; Corre, Y.; Corrigan, G.; Cortes, S.; Coster, D.; Couchman, A. S.; Cox, M. P.; Craciunescu, T.; Cramp, S.; Craven, R.; Crisanti, F.; Croci, G.; Croft, D.; Crombe, K.; Crowe, R.; Cruz, N.; Cseh, G.; Cufar, A.; Cullen, A.; Curuia, M.; Czarnecka, A.; Dabirikhah, H.; Dalgliesh, P.; Dalley, S.; Dankowski, J.; Darrow, D.; Davies, O.; Davis, W.; Day, C.; Day, I. E.; De Bock, M.; Castro, A. de; Cal, E. de la; Luna, E. de la; De Masi, G.; Pablos, J. L. de; De Temmerman, G.; De Tommasi, G.; Vries, P. de; Deakin, K.; Deane, J.; Agostini, F. D.; Dejarnac, R.; Delabie, E.; Harder, N. den; Dendy, R. O.; Denis, J.; Denner, P.; Devaux, S.; Devynck, P.; Di Maio, F.; Di Siena, A.; Di Troia, C.; Dinca, P.; D’Inca, R.; Ding, B.; Dittmar, T.; Doerk, H.; Doerner, R. P.; Donne, T.; Dorling, S. E.; Dormido-Canto, S.; Doswon, S.; Douai, D.; Doyle, P. T.; Drenik, A.; Drewelow, P.; Drews, P.; Duckworth, P.; Dumont, R.; Dumortier, P.; Dunai, D.; Dunne, M.; Duran, I.; Durodie, F.; Dutta, P.; Duval, B. P.; Dux, R.; Dylst, K.; Dzysiuk, N.; Edappala, P. V.; Edmond, J.; Edwards, A. M.; Edwards, J.; Eich, T.; Ekedahl, A.; El-Jorf, R.; Elsmore, C. G.; Enachescu, M.; Ericsson, G.; Eriksson, F.; Eriksson, J.; Eriksson, L. G.; Esposito, B.; Esquembri, S.; Esser, H. G.; Esteve, D.; Evans, B.; Evans, G. E.; Evison, G.; Ewart, G. D.; Fagan, D.; Faitsch, M.; Falie, D.; Fanni, A.; Fasoli, A.; Faustin, J. M.; Fawlk, N.; Fazendeiro, L.; Fedorczak, N.; Felton, R. C.; Fenton, K.; Fernades, A.; Fernandes, H.; Ferreira, J.; Fessey, J. A.; Fevrier, O.; Ficker, O.; Field, A.; Fietz, S.; Figueiredo, A.; Figueiredo, J.; Fil, A.; Finburg, P.; Firdaouss, M.; Fischer, U.; Fittill, L.; Fitzgerald, M.; Flammini, D.; Flanagan, J.; Fleming, C.; Flinders, K.; Fonnesu, N.; Fontdecaba, J. M.; Formisano, A.; Forsythe, L.; Fortuna, L.; Fortuna-Zalesna, E.; Fortune, M.; Foster, S.; Franke, T.; Franklin, T.; Frasca, M.; Frassinetti, L.; Freisinger, M.; Fresa, R.; Frigione, D.; Fuchs, V.; Fuller, D.; Futatani, S.; Fyvie, J.; Gal, K.; Galassi, D.; Galazka, K.; Galdon-Quiroga, J.; Gallagher, J.; Gallart, D.; Galvao, R.; Gao, X.; Gao, Y.; Garcia, J.; Garcia-Carrasco, A.; Garcia-Munoz, M.; Gardarein, J.-L.; Garzotti, L.; Gaudio, P.; Gauthier, E.; Gear, D. F.; Gee, S. J.; Geiger, B.; Gelfusa, M.; Gerasimov, S.; Gervasini, G.; Gethins, M.; Ghani, Z.; Ghate, M.; Gherendi, M.; Giacalone, J. C.; Giacomelli, L.; Gibson, C. S.; Giegerich, T.; Gil, C.; Gil, L.; Gilligan, S.; Gin, D.; Giovannozzi, E.; Girardo, J. B.; Giroud, C.; Giruzzi, G.; Gloeggler, S.; Godwin, J.; Goff, J.; Gohil, P.; Goloborod’ko, V.; Gomes, R.; Goncalves, B.; Goniche, M.; Goodliffe, M.; Goodyear, A.; Gorini, G.; Gosk, M.; Goulding, R.; Goussarov, A.; Gowland, R.; Graham, B.; Graham, M. E.; Graves, J. P.; Grazier, N.; Grazier, P.; Green, N. R.; Greuner, H.; Grierson, B.; Griph, F. S.; Grisolia, C.; Grist, D.; Groth, M.; Grove, R.; Grundy, C. N.; Grzonka, J.; Guard, D.; Guerard, C.; Guillemaut, C.; Guirlet, R.; Gurl, C.; Utoh, H. H.; Hackett, L. J.; Hacquin, S.; Hagar, A.; Hager, R.; Hakola, A.; Halitovs, M.; Hall, S. J.; Cook, S. P. H.; Hamlyn-Harris, C.; Hammond, K.; Harrington, C.; Harrison, J.; Harting, D.; Hasenbeck, F.; Hatano, Y.; Hatch, D. R.; Haupt, T. D. V.; Hawes, J.; Hawkes, N. C.; Hawkins, J.; Hawkins, P.; Haydon, P. W.; Hayter, N.; Hazel, S.; Heesterman, P. J. L.; Heinola, K.; Hellesen, C.; Hellsten, T.; Helou, W.; Hemming, O. N.; Hender, T. C.; Henderson, M.; Henderson, S. S.; Henriques, R.; Hepple, D.; Hermon, G.; Hertout, P.; Hidalgo, C.; Highcock, E. G.; Hill, M.; Hillairet, J.; Hillesheim, J.; Hillis, D.; Hizanidis, K.; Hjalmarsson, A.; Hobirk, J.; Hodille, E.; Hogben, C. H. A.; Hogeweij, G. M. D.; Hollingsworth, A.; Hollis, S.; Homfray, D. A.; Horacek, J.; Hornung, G.; Horton, A. R.; Horton, L. D.; Horvath, L.; Hotchin, S. P.; Hough, M. R.; Howarth, P. J.; Hubbard, A.; Huber, A.; Huber, V.; Huddleston, T. M.; Hughes, M.; Huijsmans, G. T. A.; Hunter, C. L.; Huynh, P.; Hynes, A. M.; Iglesias, D.; Imazawa, N.; Imbeaux, F.; Imrisek, M.; Incelli, M.; Innocente, P.; Irishkin, M.; Ivanova-Stanik, I.; Jachmich, S.; Jacobsen, A. S.; Jacquet, P.; Jansons, J.; Jardin, A.; Jarvinen, A.; Jaulmes, F.; Jednorog, S.; Jenkins, I.; Jeong, C.; Jepu, I.; Joffrin, E.; Johnson, R.; Johnson, T.; Johnston, J.; Joita, L.; Jones, G.; Jones, T. T. C.; Hoshino, K. K.; Kallenbach, A.; Kamiya, K.; Kaniewski, J.; Kantor, A.; Kappatou, A.; Karhunen, J.; Karkinsky, D.; Karnowska, I.; Kaufman, M.; Kaveney, G.; Kazakov, Y.; Kazantzidis, V.; Keeling, D. L.; Keenan, T.; Keep, J.; Kempenaars, M.; Kennedy, C.; Kenny, D.; Kent, J.; Kent, O. N.; Khilkevich, E.; Kim, H. T.; Kim, H. S.; Kinch, A.; King, C.; King, D.; King, R. F.; Kinna, D. J.; Kiptily, V.; Kirk, A.; Kirov, K.; Kirschner, A.; Kizane, G.; Klepper, C.; Klix, A.; Knight, P.; Knipe, S. J.; Knott, S.; Kobuchi, T.; Koechl, F.; Kocsis, G.; Kodeli, I.; Kogan, L.; Kogut, D.; Koivuranta, S.; Kominis, Y.; Koeppen, M.; Kos, B.; Koskela, T.; Koslowski, H. R.; Koubiti, M.; Kovari, M.; Kowalska-Strzeciwilk, E.; Krasilnikov, A.; Krasilnikov, V.; Krawczyk, N.; Kresina, M.; Krieger, K.; Krivska, A.; Kruezi, U.; Ksiazek, I.; Kukushkin, A.; Kundu, A.; Kurki-Suonio, T.; Kwak, S.; Kwiatkowski, R.; Kwon, O. J.; Laguardia, L.; Lahtinen, A.; Laing, A.; Lam, N.; Lambertz, H. T.; Lane, C.; Lang, P. 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R.; Mertens, P.; Meshchaninov, S.; Messiaen, A.; Meyer, H.; Mianowski, S.; Michling, R.; Middleton-Gear, D.; Miettunen, J.; Militello, F.; Militello-Asp, E.; Miloshevsky, G.; Mink, F.; Minucci, S.; Miyoshi, Y.; Mlynar, J.; Molina, D.; Monakhov, I.; Moneti, M.; Mooney, R.; Moradi, S.; Mordijck, S.; Moreira, L.; Moreno, R.; Moro, F.; Morris, A. W.; Morris, J.; Moser, L.; Mosher, S.; Moulton, D.; Murari, A.; Muraro, A.; Murphy, S.; Asakura, N. N.; Na, Y. S.; Nabais, F.; Naish, R.; Nakano, T.; Nardon, E.; Naulin, V.; Nave, M. F. F.; Nedzelski, I.; Nemtsev, G.; Nespoli, F.; Neto, A.; Neu, R.; Neverov, V. S.; Newman, M.; Nicholls, K. J.; Nicolas, T.; Nielsen, A. H.; Nielsen, P.; Nilsson, E.; Nishijima, D.; Noble, C.; Nocente, M.; Nodwell, D.; Nordlund, K.; Nordman, H.; Nouailletas, R.; Nunes, I.; Oberkofler, M.; Odupitan, T.; Ogawa, M. T.; O’Gorman, T.; Okabayashi, M.; Olney, R.; Omolayo, O.; O’Mullane, M.; Ongena, J.; Orsitto, F.; Orszagh, J.; Oswuigwe, B. I.; Otin, R.; Owen, A.; Paccagnella, R.; Pace, N.; Pacella, D.; Packer, L. W.; Page, A.; Pajuste, E.; Palazzo, S.; Pamela, S.; Panja, S.; Papp, P.; Paprok, R.; Parail, V.; Park, M.; Diaz, F. P.; Parsons, M.; Pasqualotto, R.; Patel, A.; Pathak, S.; Paton, D.; Patten, H.; Pau, A.; Pawelec, E.; Soldan, C. P.; Peackoc, A.; Pearson, I. J.; Pehkonen, S.-P.; Peluso, E.; Penot, C.; Pereira, A.; Pereira, R.; Puglia, P. P. P.; Thun, C. P. von; Peruzzo, S.; Peschanyi, S.; Peterka, M.; Petersson, P.; Petravich, G.; Petre, A.; Petrella, N.; Petrzilka, V.; Peysson, Y.; Pfefferle, D.; Philipps, V.; Pillon, M.; Pintsuk, G.; Piovesan, P.; Pires dos Reis, A.; Piron, L.; Pironti, A.; Pisano, F.; Pitts, R.; Pizzo, F.; Plyusnin, V.; Pomaro, N.; Pompilian, O. G.; Pool, P. J.; Popovichev, S.; Porfiri, M. T.; Porosnicu, C.; Porton, M.; Possnert, G.; Potzel, S.; Powell, T.; Pozzi, J.; Prajapati, V.; Prakash, R.; Prestopino, G.; Price, D.; Price, M.; Price, R.; Prior, P.; Proudfoot, R.; Pucella, G.; Puglia, P.; Puiatti, M. E.; Pulley, D.; Purahoo, K.; Puetterich, T.; Rachlew, E.; Rack, M.; Ragona, R.; Rainford, M. S. J.; Rakha, A.; Ramogida, G.; Ranjan, S.; Rapson, C. J.; Rasmussen, J. J.; Rathod, K.; Ratta, G.; Ratynskaia, S.; Ravera, G.; Rayner, C.; Rebai, M.; Reece, D.; Reed, A.; Refy, D.; Regan, B.; Regana, J.; Reich, M.; Reid, N.; Reimold, F.; Reinhart, M.; Reinke, M.; Reiser, D.; Rendell, D.; Reux, C.; Reyes Cortes, S. D. A.; Reynolds, S.; Riccardo, V.; Richardson, N.; Riddle, K.; Rigamonti, D.; Rimini, F. G.; Risner, J.; Riva, M.; Roach, C.; Robins, R. J.; Robinson, S. A.; Robinson, T.; Robson, D. W.; Roccella, R.; Rodionov, R.; Rodrigues, P.; Rodriguez, J.; Rohde, V.; Romanelli, F.; Romanelli, M.; Romanelli, S.; Romazanov, J.; Rowe, S.; Rubel, M.; Rubinacci, G.; Rubino, G.; Ruchko, L.; Ruiz, M.; Ruset, C.; Rzadkiewicz, J.; Saarelma, S.; Sabot, R.; Safi, E.; Sagar, P.; Saibene, G.; Saint-Laurent, F.; Salewski, M.; Salmi, A.; Salmon, R.; Salzedas, F.; Samaddar, D.; Samm, U.; Sandiford, D.; Santa, P.; Santala, M. I. K.; Santos, B.; Santucci, A.; Sartori, F.; Sartori, R.; Sauter, O.; Scannell, R.; Schlummer, T.; Schmid, K.; Schmidt, V.; Schmuck, S.; Schneider, M.; Schoepf, K.; Schworer, D.; Scott, S. D.; Sergienko, G.; Sertoli, M.; Shabbir, A.; Sharapov, S. E.; Shaw, A.; Shaw, R.; Sheikh, H.; Shepherd, A.; Shevelev, A.; Shumack, A.; Sias, G.; Sibbald, M.; Sieglin, B.; Silburn, S.; Silva, A.; Silva, C.; Simmons, P. A.; Simpson, J.; Simpson-Hutchinson, J.; Sinha, A.; Sipila, S. K.; Sips, A. C. C.; Siren, P.; Sirinelli, A.; Sjostrand, H.; Skiba, M.; Skilton, R.; Slabkowska, K.; Slade, B.; Smith, N.; Smith, P. G.; Smith, R.; Smith, T. J.; Smithies, M.; Snoj, L.; Soare, S.; Solano, E. R.; Somers, A.; Sommariva, C.; Sonato, P.; Sopplesa, A.; Sousa, J.; Sozzi, C.; Spagnolo, S.; Spelzini, T.; Spineanu, F.; Stables, G.; Stamatelatos, I.; Stamp, M. F.; Staniec, P.; Stankunas, G.; Stan-Sion, C.; Stead, M. J.; Stefanikova, E.; Stepanov, I.; Stephen, A. V.; Stephen, M.; Stevens, A.; Stevens, B. D.; Strachan, J.; Strand, P.; Strauss, H. R.; Strom, P.; Stubbs, G.; Studholme, W.; Subba, F.; Summers, H. P.; Svensson, J.; Swiderski, L.; Szabolics, T.; Szawlowski, M.; Szepesi, G.; Suzuki, T. T.; Tal, B.; Tala, T.; Talbot, A. R.; Talebzadeh, S.; Taliercio, C.; Tamain, P.; Tame, C.; Tang, W.; Tardocchi, M.; Taroni, L.; Taylor, D.; Taylor, K. A.; Tegnered, D.; Telesca, G.; Teplova, N.; Terranova, D.; Testa, D.; Tholerus, E.; Thomas, J.; Thomas, J. 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Nuclear fusion, 59 (1), Art. Nr.: 016004. doi:10.1088/1741-4326/aaea1e
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JET Contributors; Frassinetti, L.; Dunne, M. G.; Sheikh, U.; Saarelma, S.; Roach, C. M.; Stefanikova, E.; Maggi, C.; Horvath, L.; Pamela, S.; Luna, E. de la; Wolfrum, E.; Bernert, M.; Blanchard, P.; Labit, B.; Merle, A.; Guimarais, L.; Coda, S.; Meyer, H.; Hillesheim, J. C.; Abduallev, S.; Abhangi, M.; Abreu, P.; Afzal, M.; Aggarwal, K. M.; Ahlgren, T.; Ahn, J. H.; Aho-Mantila, L.; Aiba, N.; Airila, M.; Albanese, R.; Aldred, V.; Alegre, D.; Alessi, E.; Aleynikov, P.; Alfier, A.; Alkseev, A.; Allinson, M.; Alper, B.; Alves, E.; Ambrosino, G.; Ambrosino, R.; Amicucci, L.; Amosov, V.; Sunden, E. A.; Angelone, M.; Anghel, M.; Angioni, C.; Appel, L.; Appelbee, C.; Arena, P.; Ariola, M.; Arnichand, H.; Arshad, S.; Ash, A.; Ashikawa, N.; Aslanyan, V.; Asunta, O.; Auriemma, F.; Austin, Y.; Avotina, L.; Axton, M. D.; Ayres, C.; Bacharis, M.; Baciero, A.; Baiao, D.; Bailey, S.; Baker, A.; Balboa, I.; Balden, M.; Balshaw, N.; Bament, R.; Banks, J. W.; Baranov, Y. F.; Barnard, M. A.; Barnes, D.; Barnes, M.; Barnsley, R.; Wiechec, A. B.; Orte, L. B.; Baruzzo, M.; Basiuk, V.; Bassan, M.; Bastow, R.; Batista, A.; Batistoni, P.; Baughan, R.; Bauvir, B.; Baylor, L.; Bazylev, B.; Beal, J.; Beaumont, P. S.; Beckers, M.; Beckett, B.; Becoulet, A.; Bekris, N.; Beldishevski, M.; Bell, K.; Belli, F.; Bellinger, M.; Belonohy, E.; Ben Ayed, N.; Benterman, N. A.; Bergsaker, H.; Bernardo, J.; Bernert, M.; Berry, M.; Bertalot, L.; Besliu, C.; Beurskens, M.; Bieg, B.; Bielecki, J.; Biewer, T.; Bigi, M.; Bilkova, P.; Binda, F.; Bisoffi, A.; Bizarro, J. P. S.; Bjorkas, C.; Blackburn, J.; Blackman, K.; Blackman, T. R.; Blanchard, P.; Blatchford, P.; Bobkov, V.; Boboc, A.; Bodnar, G.; Bogar, O.; Bolshakova, I.; Bolzonella, T.; Bonanomi, N.; Bonelli, F.; Boom, J.; Booth, J.; Borba, D.; Borodin, D.; Borodkina, I.; Botrugno, A.; Bottereau, C.; Boulting, P.; Bourdelle, C.; Bowden, M.; Bower, C.; Bowman, C.; Boyce, T.; Boyd, C.; Boyer, H. J.; Bradshaw, J. M. A.; Braic, V.; Bravanec, R.; Breizman, B.; Bremond, S.; Brennan, P. D.; Breton, S.; Brett, A.; Brezinsek, S.; Bright, M. D. J.; Brix, M.; Broeckx, W.; Brombin, M.; Broslawski, A.; Brown, D. P. D.; Brown, M.; Bruno, E.; Bucalossi, J.; Buch, J.; Buchanan, J.; Buckley, M. A.; Budny, R.; Bufferand, H.; Bulman, M.; Bulmer, N.; Bunting, P.; Buratti, P.; Burckhart, A.; Buscarino, A.; Busse, A.; Butler, N. K.; Bykov, I.; Byrne, J.; Cahyna, P.; Calabro, G.; Calvo, I.; Camenen, Y.; Camp, P.; Campling, D. C.; Cane, J.; Cannas, B.; Capel, A. J.; Card, P. J.; Cardinali, A.; Carman, P.; Carr, M.; Carralero, D.; Carraro, L.; Carvalho, B. B.; Carvalho, I.; Carvalho, P.; Casson, F. J.; Castaldo, C.; Catarino, N.; Caumont, J.; Causa, F.; Cavazzana, R.; Cave-Ayland, K.; Cavinato, M.; Cecconello, M.; Ceccuzzi, S.; Cecil, E.; Cenedese, A.; Cesario, R.; Challis, C. D.; Chandler, M.; Chandra, D.; Chang, C. S.; Chankin, A.; Chapman, I. T.; Chapman, S. C.; Chernyshova, M.; Chitarin, G.; Ciraolo, G.; Ciric, D.; Citrin, J.; Clairet, F.; Clark, E.; Clark, M.; Clarkson, R.; Clatworthy, D.; Clements, C.; Cleverly, M.; Coad, J. P.; Coates, P. A.; Cobalt, A.; Coccorese, V.; Cocilovo, V.; Coda, S.; Coelho, R.; Coenen, J. W.; Coffey, I.; Colas, L.; Collins, S.; Conka, D.; Conroy, S.; Conway, N.; Coombs, D.; Cooper, D.; Cooper, S. R.; Corradino, C.; Corre, Y.; Corrigan, G.; Cortes, S.; Coster, D.; Couchman, A. S.; Cox, M. P.; Craciunescu, T.; Cramp, S.; Craven, R.; Crisanti, F.; Croci, G.; Croft, D.; Crombe, K.; Crowe, R.; Cruz, N.; Cseh, G.; Cufar, A.; Cullen, A.; Curuia, M.; Czarnecka, A.; Dabirikhah, H.; Dalgliesh, P.; Dalley, S.; Dankowski, J.; Darrow, D.; Davies, O.; Davis, W.; Day, C.; Day, I. E.; De Bock, M.; Castro, A. de; Cal, E. de la; Luna, E. de la; De Masi, G.; Pablos, J. L. de; De Temmerman, G.; De Tommasi, G.; Vries, P. de; Deakin, K.; Deane, J.; Agostini, F. D.; Dejarnac, R.; Delabie, E.; Harder, N. den; Dendy, R. O.; Denis, J.; Denner, P.; Devaux, S.; Devynck, P.; Di Maio, F.; Di Siena, A.; Di Troia, C.; Dinca, P.; D’Inca, R.; Ding, B.; Dittmar, T.; Doerk, H.; Doerner, R. P.; Donne, T.; Dorling, S. E.; Dormido-Canto, S.; Doswon, S.; Douai, D.; Doyle, P. T.; Drenik, A.; Drewelow, P.; Drews, P.; Duckworth, P.; Dumont, R.; Dumortier, P.; Dunai, D.; Dunne, M.; Duran, I.; Durodie, F.; Dutta, P.; Duval, B. P.; Dux, R.; Dylst, K.; Dzysiuk, N.; Edappala, P. V.; Edmond, J.; Edwards, A. M.; Edwards, J.; Eich, T.; Ekedahl, A.; El-Jorf, R.; Elsmore, C. G.; Enachescu, M.; Ericsson, G.; Eriksson, F.; Eriksson, J.; Eriksson, L. G.; Esposito, B.; Esquembri, S.; Esser, H. G.; Esteve, D.; Evans, B.; Evans, G. E.; Evison, G.; Ewart, G. D.; Fagan, D.; Faitsch, M.; Falie, D.; Fanni, A.; Fasoli, A.; Faustin, J. M.; Fawlk, N.; Fazendeiro, L.; Fedorczak, N.; Felton, R. C.; Fenton, K.; Fernades, A.; Fernandes, H.; Ferreira, J.; Fessey, J. A.; Fevrier, O.; Ficker, O.; Field, A.; Fietz, S.; Figueiredo, A.; Figueiredo, J.; Fil, A.; Finburg, P.; Firdaouss, M.; Fischer, U.; Fittill, L.; Fitzgerald, M.; Flammini, D.; Flanagan, J.; Fleming, C.; Flinders, K.; Fonnesu, N.; Fontdecaba, J. M.; Formisano, A.; Forsythe, L.; Fortuna, L.; Fortuna-Zalesna, E.; Fortune, M.; Foster, S.; Franke, T.; Franklin, T.; Frasca, M.; Frassinetti, L.; Freisinger, M.; Fresa, R.; Frigione, D.; Fuchs, V.; Fuller, D.; Futatani, S.; Fyvie, J.; Gal, K.; Galassi, D.; Galazka, K.; Galdon-Quiroga, J.; Gallagher, J.; Gallart, D.; Galvao, R.; Gao, X.; Gao, Y.; Garcia, J.; Garcia-Carrasco, A.; Garcia-Munoz, M.; Gardarein, J.-L.; Garzotti, L.; Gaudio, P.; Gauthier, E.; Gear, D. F.; Gee, S. J.; Geiger, B.; Gelfusa, M.; Gerasimov, S.; Gervasini, G.; Gethins, M.; Ghani, Z.; Ghate, M.; Gherendi, M.; Giacalone, J. C.; Giacomelli, L.; Gibson, C. S.; Giegerich, T.; Gil, C.; Gil, L.; Gilligan, S.; Gin, D.; Giovannozzi, E.; Girardo, J. B.; Giroud, C.; Giruzzi, G.; Gloeggler, S.; Godwin, J.; Goff, J.; Gohil, P.; Goloborod’ko, V.; Gomes, R.; Goncalves, B.; Goniche, M.; Goodliffe, M.; Goodyear, A.; Gorini, G.; Gosk, M.; Goulding, R.; Goussarov, A.; Gowland, R.; Graham, B.; Graham, M. E.; Graves, J. P.; Grazier, N.; Grazier, P.; Green, N. R.; Greuner, H.; Grierson, B.; Griph, F. S.; Grisolia, C.; Grist, D.; Groth, M.; Grove, R.; Grundy, C. N.; Grzonka, J.; Guard, D.; Guerard, C.; Guillemaut, C.; Guirlet, R.; Gurl, C.; Utoh, H. H.; Hackett, L. J.; Hacquin, S.; Hagar, A.; Hager, R.; Hakola, A.; Halitovs, M.; Hall, S. J.; Cook, S. P. H.; Hamlyn-Harris, C.; Hammond, K.; Harrington, C.; Harrison, J.; Harting, D.; Hasenbeck, F.; Hatano, Y.; Hatch, D. R.; Haupt, T. D. V.; Hawes, J.; Hawkes, N. C.; Hawkins, J.; Hawkins, P.; Haydon, P. W.; Hayter, N.; Hazel, S.; Heesterman, P. J. L.; Heinola, K.; Hellesen, C.; Hellsten, T.; Helou, W.; Hemming, O. N.; Hender, T. C.; Henderson, M.; Henderson, S. S.; Henriques, R.; Hepple, D.; Hermon, G.; Hertout, P.; Hidalgo, C.; Highcock, E. G.; Hill, M.; Hillairet, J.; Hillesheim, J.; Hillis, D.; Hizanidis, K.; Hjalmarsson, A.; Hobirk, J.; Hodille, E.; Hogben, C. H. A.; Hogeweij, G. M. D.; Hollingsworth, A.; Hollis, S.; Homfray, D. A.; Horacek, J.; Hornung, G.; Horton, A. R.; Horton, L. D.; Horvath, L.; Hotchin, S. P.; Hough, M. R.; Howarth, P. J.; Hubbard, A.; Huber, A.; Huber, V.; Huddleston, T. M.; Hughes, M.; Huijsmans, G. T. A.; Hunter, C. L.; Huynh, P.; Hynes, A. M.; Iglesias, D.; Imazawa, N.; Imbeaux, F.; Imrisek, M.; Incelli, M.; Innocente, P.; Irishkin, M.; Ivanova-Stanik, I.; Jachmich, S.; Jacobsen, A. S.; Jacquet, P.; Jansons, J.; Jardin, A.; Jarvinen, A.; Jaulmes, F.; Jednorog, S.; Jenkins, I.; Jeong, C.; Jepu, I.; Joffrin, E.; Johnson, R.; Johnson, T.; Johnston, J.; Joita, L.; Jones, G.; Jones, T. T. C.; Hoshino, K. K.; Kallenbach, A.; Kamiya, K.; Kaniewski, J.; Kantor, A.; Kappatou, A.; Karhunen, J.; Karkinsky, D.; Karnowska, I.; Kaufman, M.; Kaveney, G.; Kazakov, Y.; Kazantzidis, V.; Keeling, D. L.; Keenan, T.; Keep, J.; Kempenaars, M.; Kennedy, C.; Kenny, D.; Kent, J.; Kent, O. N.; Khilkevich, E.; Kim, H. T.; Kim, H. S.; Kinch, A.; King, C.; King, D.; King, R. F.; Kinna, D. J.; Kiptily, V.; Kirk, A.; Kirov, K.; Kirschner, A.; Kizane, G.; Klepper, C.; Klix, A.; Knight, P.; Knipe, S. J.; Knott, S.; Kobuchi, T.; Koechl, F.; Kocsis, G.; Kodeli, I.; Kogan, L.; Kogut, D.; Koivuranta, S.; Kominis, Y.; Koeppen, M.; Kos, B.; Koskela, T.; Koslowski, H. R.; Koubiti, M.; Kovari, M.; Kowalska-Strzeciwilk, E.; Krasilnikov, A.; Krasilnikov, V.; Krawczyk, N.; Kresina, M.; Krieger, K.; Krivska, A.; Kruezi, U.; Ksiazek, I.; Kukushkin, A.; Kundu, A.; Kurki-Suonio, T.; Kwak, S.; Kwiatkowski, R.; Kwon, O. J.; Laguardia, L.; Lahtinen, A.; Laing, A.; Lam, N.; Lambertz, H. T.; Lane, C.; Lang, P. T.; Lanthaler, S.; Lapins, J.; Lasa, A.; Last, J. R.; Laszynska, E.; Lawless, R.; Lawson, A.; Lawson, K. D.; Lazaros, A.; Lazzaro, E.; Leddy, J.; Lee, S.; Lefebvre, X.; Leggate, H. J.; Lehmann, J.; Lehnen, M.; Leichtle, D.; Leichuer, P.; Leipold, F.; Lengar, I.; Lennholm, M.; Lerche, E.; Lescinskis, A.; Lesnoj, S.; Letellier, E.; Leyland, M.; Leysen, W.; Li, L.; Liang, Y.; Likonen, J.; Linke, J.; Linsmeier, C.; Lipschultz, B.; Liu, G.; Liu, Y.; Lo Schiavo, V. P.; Loarer, T.; Loarte, A.; Lobel, R. C.; Lomanowski, B.; Lomas, P. J.; Lonnroth, J.; Lopez, J. M.; Lopez-Razola, J.; Lorenzini, R.; Losada, U.; Lovell, J. J.; Loving, A. B.; Lowry, C.; Luce, T.; Lucock, R. M. A.; Lukin, A.; Luna, C.; Lungaroni, M.; Lungu, C. P.; Lungu, M.; Lunniss, A.; Lupelli, I.; Lyssoivan, A.; Macdonald, N.; Macheta, P.; Maczewa, K.; Magesh, B.; Maget, P.; Maggi, C.; Maier, H.; Mailloux, J.; Makkonen, T.; Makwana, R.; Malaquias, A.; Malizia, A.; Manas, P.; Manning, A.; Manso, M. E.; Mantica, P.; Mantsinen, M.; Manzanares, A.; Maquet, P.; Marandet, Y.; Marcenko, N.; Marchetto, C.; Marchuk, O.; Marinelli, M.; Marinucci, M.; Markovic, T.; Marocco, D.; Marot, L.; Marren, C. A.; Marshal, R.; Martin, A.; Martin, Y.; Martin de Aguilera, A.; Martinez, F. J.; Martin-Solis, J. R.; Martynova, Y.; Maruyama, S.; Masiello, A.; Maslov, M.; Matejcik, S.; Mattei, M.; Matthews, G. F.; Maviglia, F.; Mayer, M.; Mayoral, M. L.; May-Smith, T.; Mazon, D.; Mazzotta, C.; McAdams, R.; McCarthy, P. J.; McClements, K. G.; McCormack, O.; McCullen, P. A.; McDonald, D.; McIntosh, S.; McKean, R.; McKehon, J.; Meadows, R. C.; Meakins, A.; Medina, F.; Medland, M.; Medley, S.; Meigh, S.; Meigs, A. G.; Meisl, G.; Meitner, S.; Meneses, L.; Menmuir, S.; Mergia, K.; Merrigan, I. R.; Mertens, P.; Meshchaninov, S.; Messiaen, A.; Meyer, H.; Mianowski, S.; Michling, R.; Middleton-Gear, D.; Miettunen, J.; Militello, F.; Militello-Asp, E.; Miloshevsky, G.; Mink, F.; Minucci, S.; Miyoshi, Y.; Mlynar, J.; Molina, D.; Monakhov, I.; Moneti, M.; Mooney, R.; Moradi, S.; Mordijck, S.; Moreira, L.; Moreno, R.; Moro, F.; Morris, A. W.; Morris, J.; Moser, L.; Mosher, S.; Moulton, D.; Murari, A.; Muraro, A.; Murphy, S.; Asakura, N. N.; Na, Y. S.; Nabais, F.; Naish, R.; Nakano, T.; Nardon, E.; Naulin, V.; Nave, M. F. F.; Nedzelski, I.; Nemtsev, G.; Nespoli, F.; Neto, A.; Neu, R.; Neverov, V. S.; Newman, M.; Nicholls, K. J.; Nicolas, T.; Nielsen, A. H.; Nielsen, P.; Nilsson, E.; Nishijima, D.; Noble, C.; Nocente, M.; Nodwell, D.; Nordlund, K.; Nordman, H.; Nouailletas, R.; Nunes, I.; Oberkofler, M.; Odupitan, T.; Ogawa, M. T.; O’Gorman, T.; Okabayashi, M.; Olney, R.; Omolayo, O.; O’Mullane, M.; Ongena, J.; Orsitto, F.; Orszagh, J.; Oswuigwe, B. I.; Otin, R.; Owen, A.; Paccagnella, R.; Pace, N.; Pacella, D.; Packer, L. W.; Page, A.; Pajuste, E.; Palazzo, S.; Pamela, S.; Panja, S.; Papp, P.; Paprok, R.; Parail, V.; Park, M.; Diaz, F. P.; Parsons, M.; Pasqualotto, R.; Patel, A.; Pathak, S.; Paton, D.; Patten, H.; Pau, A.; Pawelec, E.; Soldan, C. P.; Peackoc, A.; Pearson, I. J.; Pehkonen, S.-P.; Peluso, E.; Penot, C.; Pereira, A.; Pereira, R.; Puglia, P. P. P.; Thun, C. P. von; Peruzzo, S.; Peschanyi, S.; Peterka, M.; Petersson, P.; Petravich, G.; Petre, A.; Petrella, N.; Petrzilka, V.; Peysson, Y.; Pfefferle, D.; Philipps, V.; Pillon, M.; Pintsuk, G.; Piovesan, P.; Pires dos Reis, A.; Piron, L.; Pironti, A.; Pisano, F.; Pitts, R.; Pizzo, F.; Plyusnin, V.; Pomaro, N.; Pompilian, O. G.; Pool, P. J.; Popovichev, S.; Porfiri, M. T.; Porosnicu, C.; Porton, M.; Possnert, G.; Potzel, S.; Powell, T.; Pozzi, J.; Prajapati, V.; Prakash, R.; Prestopino, G.; Price, D.; Price, M.; Price, R.; Prior, P.; Proudfoot, R.; Pucella, G.; Puglia, P.; Puiatti, M. E.; Pulley, D.; Purahoo, K.; Puetterich, T.; Rachlew, E.; Rack, M.; Ragona, R.; Rainford, M. S. J.; Rakha, A.; Ramogida, G.; Ranjan, S.; Rapson, C. J.; Rasmussen, J. J.; Rathod, K.; Ratta, G.; Ratynskaia, S.; Ravera, G.; Rayner, C.; Rebai, M.; Reece, D.; Reed, A.; Refy, D.; Regan, B.; Regana, J.; Reich, M.; Reid, N.; Reimold, F.; Reinhart, M.; Reinke, M.; Reiser, D.; Rendell, D.; Reux, C.; Reyes Cortes, S. D. A.; Reynolds, S.; Riccardo, V.; Richardson, N.; Riddle, K.; Rigamonti, D.; Rimini, F. G.; Risner, J.; Riva, M.; Roach, C.; Robins, R. J.; Robinson, S. A.; Robinson, T.; Robson, D. W.; Roccella, R.; Rodionov, R.; Rodrigues, P.; Rodriguez, J.; Rohde, V.; Romanelli, F.; Romanelli, M.; Romanelli, S.; Romazanov, J.; Rowe, S.; Rubel, M.; Rubinacci, G.; Rubino, G.; Ruchko, L.; Ruiz, M.; Ruset, C.; Rzadkiewicz, J.; Saarelma, S.; Sabot, R.; Safi, E.; Sagar, P.; Saibene, G.; Saint-Laurent, F.; Salewski, M.; Salmi, A.; Salmon, R.; Salzedas, F.; Samaddar, D.; Samm, U.; Sandiford, D.; Santa, P.; Santala, M. I. K.; Santos, B.; Santucci, A.; Sartori, F.; Sartori, R.; Sauter, O.; Scannell, R.; Schlummer, T.; Schmid, K.; Schmidt, V.; Schmuck, S.; Schneider, M.; Schoepf, K.; Schworer, D.; Scott, S. D.; Sergienko, G.; Sertoli, M.; Shabbir, A.; Sharapov, S. E.; Shaw, A.; Shaw, R.; Sheikh, H.; Shepherd, A.; Shevelev, A.; Shumack, A.; Sias, G.; Sibbald, M.; Sieglin, B.; Silburn, S.; Silva, A.; Silva, C.; Simmons, P. A.; Simpson, J.; Simpson-Hutchinson, J.; Sinha, A.; Sipila, S. K.; Sips, A. C. C.; Siren, P.; Sirinelli, A.; Sjostrand, H.; Skiba, M.; Skilton, R.; Slabkowska, K.; Slade, B.; Smith, N.; Smith, P. G.; Smith, R.; Smith, T. J.; Smithies, M.; Snoj, L.; Soare, S.; Solano, E. R.; Somers, A.; Sommariva, C.; Sonato, P.; Sopplesa, A.; Sousa, J.; Sozzi, C.; Spagnolo, S.; Spelzini, T.; Spineanu, F.; Stables, G.; Stamatelatos, I.; Stamp, M. F.; Staniec, P.; Stankunas, G.; Stan-Sion, C.; Stead, M. J.; Stefanikova, E.; Stepanov, I.; Stephen, A. V.; Stephen, M.; Stevens, A.; Stevens, B. D.; Strachan, J.; Strand, P.; Strauss, H. R.; Strom, P.; Stubbs, G.; Studholme, W.; Subba, F.; Summers, H. P.; Svensson, J.; Swiderski, L.; Szabolics, T.; Szawlowski, M.; Szepesi, G.; Suzuki, T. T.; Tal, B.; Tala, T.; Talbot, A. R.; Talebzadeh, S.; Taliercio, C.; Tamain, P.; Tame, C.; Tang, W.; Tardocchi, M.; Taroni, L.; Taylor, D.; Taylor, K. A.; Tegnered, D.; Telesca, G.; Teplova, N.; Terranova, D.; Testa, D.; Tholerus, E.; Thomas, J.; Thomas, J. D.; Thomas, P.; Thompson, A.; Thompson, C.-A.; Thompson, V. K.; Thorne, L.; Thornton, A.; Thrysoe, A. S.; Tigwell, P. A.; Tipton, N.; Tiseanu, I.; Tojo, H.; Tokitani, M.; Tolias, P.; Tomes, M.; Tonner, P.; Towndrow, M.; Trimble, P.; Tripsky, M.; Tsalas, M.; Tsavalas, P.; Jun, D. T.; Turner, I.; Turner, M. M.; Turnyanskiy, M.; Tvalashvili, G.; Tyrrell, S. G. J.; Uccello, A.; Ul-Abidin, Z.; Uljanovs, J.; Ulyatt, D.; Urano, H.; Uytdenhouwen, I.; Vadgama, A. P.; Valcarcel, D.; Valentinuzzi, M.; Valisa, M.; Olivares, P. V.; Valovic, M.; Van De Mortel, M.; Van Eester, D.; Van Renterghem, W.; Rooij, G. J. van; Varje, J.; Varoutis, S.; Vartanian, S.; Vasava, K.; Vasilopoulou, T.; Vega, J.; Verdoolaege, G.; Verhoeven, R.; Verona, C.; Rinati, G. V.; Veshchev, E.; Vianello, N.; Vicente, J.; Viezzer, E.; Villari, S.; Villone, F.; Vincenzi, P.; Vinyar, I.; Viola, B.; Vitins, A.; Vizvary, Z.; Vlad, M.; Voitsekhovitch, I.; Vondracek, P.; Vora, N.; Vu, T.; Pires de Sa, W. W.; Wakeling, B.; Waldon, C. W. F.; Walkden, N.; Walker, M.; Walker, R.; Walsh, M.; Wang, E.; Wang, N.; Warder, S.; Warren, R. J.; Waterhouse, J.; Watkins, N. W.; Watts, C.; Wauters, T.; Weckmann, A.; Weiland, J.; Weisen, H.; Weiszflog, M.; Wellstood, C.; West, A. T.; Wheatley, M. R.; Whetham, S.; Whitehead, A. M.; Whitehead, B. D.; Widdowson, A. M.; Wiesen, S.; Wilkinson, J.; Williams, J.; Williams, M.; Wilson, A. R.; Wilson, D. J.; Wilson, H. R.; Wilson, J.; Wischmeier, M.; Withenshaw, G.; Withycombe, A.; Witts, D. M.; Wood, D.; Wood, R.; Woodley, C.; Wray, S.; Wright, J.; Wright, J. C.; Wu, J.; Wukitch, S.; Wynn, A.; Xu, T.; Yadikin, D.; Yanling, W.; Yao, L.; Yavorskij, V.; Yoo, M. G.; Young, C.; Young, D.; Young, I. D.; Young, R.; Zacks, J.; Zagorski, R.; Zaitsev, F. S.; Zanino, R.; Zarins, A.; Zastrow, K. D.; Zerbini, M.; Zhang, W.; Zhou, Y.; Zilli, E.; Zoita, V.; Zoletnik, S.; Zychor, I. (2019). Role of the pedestal position on the pedestal performance in AUG, JET-ILW and TCV and implications for ITER. (Team, ASDEX Upgrade, Team, TCV & Team, EUROfusion MST1, Hrsg.) Nuclear fusion, 59 (7), Art. Nr.: 076038. doi:10.1088/1741-4326/ab1eb9
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JET Contributors; Neverov, V. S.; Kukushkin, A. B.; Kruezi, U.; Stamp, M. F.; Weisen, H.; Joffrin, E.; Abduallev, S.; Abhangi, M.; Abreu, P.; Afzal, M.; Aggarwal, K. M.; Ahlgren, T.; Ahn, J. H.; Aho-Mantila, L.; Aiba, N.; Airila, M.; Albanese, R.; Aldred, V.; Alegre, D.; Alessi, E.; Aleynikov, P.; Alfier, A.; Alkseev, A.; Allinson, M.; Alper, B.; Alves, E.; Ambrosino, G.; Ambrosino, R.; Amicucci, L.; Amosov, V.; Sunden, E. A.; Angelone, M.; Anghel, M.; Angioni, C.; Appel, L.; Appelbee, C.; Arena, P.; Ariola, M.; Arnichand, H.; Arshad, S.; Ash, A.; Ashikawa, N.; Aslanyan, V.; Asunta, O.; Auriemma, F.; Austin, Y.; Avotina, L.; Axton, M. D.; Ayres, C.; Bacharis, M.; Baciero, A.; Baiao, D.; Bailey, S.; Baker, A.; Balboa, I.; Balden, M.; Balshaw, N.; Bament, R.; Banks, J. W.; Baranov, Y. F.; Barnard, M. A.; Barnes, D.; Barnes, M.; Barnsley, R.; Wiechec, A. B.; Orte, L. B.; Baruzzo, M.; Basiuk, V.; Bassan, M.; Bastow, R.; Batista, A.; Batistoni, P.; Baughan, R.; Bauvir, B.; Baylor, L.; Bazylev, B.; Beal, J.; Beaumont, P. S.; Beckers, M.; Beckett, B.; Becoulet, A.; Bekris, N.; Beldishevski, M.; Bell, K.; Belli, F.; Bellinger, M.; Belonohy, E.; Ben Ayed, N.; Benterman, N. A.; Bergsaker, H.; Bernardo, J.; Bernert, M.; Berry, M.; Bertalot, L.; Besliu, C.; Beurskens, M.; Bieg, B.; Bielecki, J.; Biewer, T.; Bigi, M.; Bilkova, P.; Binda, F.; Bisoffi, A.; Bizarro, J. P. S.; Bjorkas, C.; Blackburn, J.; Blackman, K.; Blackman, T. R.; Blanchard, P.; Blatchford, P.; Bobkov, V.; Boboc, A.; Bodnar, G.; Bogar, O.; Bolshakova, I.; Bolzonella, T.; Bonanomi, N.; Bonelli, F.; Boom, J.; Booth, J.; Borba, D.; Borodin, D.; Borodkina, I.; Botrugno, A.; Bottereau, C.; Boulting, P.; Bourdelle, C.; Bowden, M.; Bower, C.; Bowman, C.; Boyce, T.; Boyd, C.; Boyer, H. J.; Bradshaw, J. M. A.; Braic, V.; Bravanec, R.; Breizman, B.; Bremond, S.; Brennan, P. D.; Breton, S.; Brett, A.; Brezinsek, S.; Bright, M. D. J.; Brix, M.; Broeckx, W.; Brombin, M.; Broslawski, A.; Brown, D. P. D.; Brown, M.; Bruno, E.; Bucalossi, J.; Buch, J.; Buchanan, J.; Buckley, M. A.; Budny, R.; Bufferand, H.; Bulman, M.; Bulmer, N.; Bunting, P.; Buratti, P.; Burckhart, A.; Buscarino, A.; Busse, A.; Butler, N. K.; Bykov, I.; Byrne, J.; Cahyna, P.; Calabro, G.; Calvo, I.; Camenen, Y.; Camp, P.; Campling, D. C.; Cane, J.; Cannas, B.; Capel, A. J.; Card, P. J.; Cardinali, A.; Carman, P.; Carr, M.; Carralero, D.; Carraro, L.; Carvalho, B. B.; Carvalho, I.; Carvalho, P.; Casson, F. J.; Castaldo, C.; Catarino, N.; Caumont, J.; Causa, F.; Cavazzana, R.; Cave-Ayland, K.; Cavinato, M.; Cecconello, M.; Ceccuzzi, S.; Cecil, E.; Cenedese, A.; Cesario, R.; Challis, C. D.; Chandler, M.; Chandra, D.; Chang, C. S.; Chankin, A.; Chapman, I. T.; Chapman, S. 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Pollok, T.; Junglas, L.; Ruf, B.; Schumann, A. (2019). UnrealGT: Using Unreal Engine to Generate Ground Truth Datasets. Advances in Visual Computing : 14th International Symposium on Visual Computing, ISVC 2019, Lake Tahoe, NV, USA, October 7–9, 2019, Proceedings, Part I. Ed.: George Bebis, 670–682, Springer. doi:10.1007/978-3-030-33720-9_52
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Riese, F. M. (2019). SUSI: SUpervised Self-organIzing maps in Python. Zenodo. doi:10.5281/zenodo.2609130
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Riese, F. M.; Keller, S. (2019). Hyperspectral Regression: Code Examples. doi:10.5281/zenodo.3450676
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Riese, F. M.; Keller, S. (2019). SUSI: Supervised Self-Organizing Maps for Regression and Classification in Python.
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Riese, F. M.; Keller, S. (2019). Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2019 ISPRS) Geospatial Week 2019, Enschede, NL, June 10-14, 2019. Vol. IV-2/W5, 615–621. doi:10.5194/isprs-annals-IV-2-W5-615-2019
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Ruf, B.; Pollok, T.; Weinmann, M. (2019). Efficient Surface-Aware Semi-Global Matching with Multi-View Plane-Sweep Sampling. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-2/W7, 137–144. doi:10.5194/isprs-annals-IV-2-W7-137-2019
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Schmitz, S.; Weinmann, M.; Ruf, B. (2019). Automatic co-registration of aerial imagery and untextured model data utilizing average shading gradients. ISPRS Geospatial Week, 10-14 June 2019, Enschede, The Netherlands, 581–588, ISPRS. doi:10.5194/isprs-archives-XLII-2-W13-581-2019
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Spirig, R.; Vogt, R.; Larsen, J. A.; Feigenwinter, C.; Wicki, A.; Franceschi, J.; Parlow, E.; Adler, B.; Kalthoff, N.; Cermak, J.; Andersen, H.; Fuchs, J.; Bott, A.; Hacker, M.; Wagner, N.; Maggs-Kölling, G.; Wassenaar, T.; Seely, M. (2019). Probing the fog life-cycles in the Namib desert. Bulletin of the American Meteorological Society, 100 (12), 2491–2507. doi:10.1175/BAMS-D-18-0142.1
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Stirnberg, R.; Cermak, J.; Kotthaus, S.; Haeffelin, M.; Andersen, H.; Kim, M. (2019). Variability of air pollution (PM1) analyzed using explainable Machine Learning. Proceedings of the 9th International Workshop on Climate Informatics: CI 2019. Ed.: J. Brajard, 157–161, National Center for Atmospheric Research. doi:10.5065/y82j-f154
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Stötzer, J.; Wursthorn, S.; Keller, S. (2019). Fuzzy Estimation of Link Travel Time from a Digital Elevation Model and Road Hierarchy Level. Proceedings of the 5th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM), Heraklion, GR, May 3-5, 2019. Vol. 1, 15–25, SciTePress. doi:10.5220/0007655800150025
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Ulrich, M.; Follmann, P.; Neudeck, J.-H. (2019). A comparison of shape-based matching with deep-learning-based object detection. Technisches Messen, 86 (11), 685–698. doi:10.1515/teme-2019-0076
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Ulrich, M.; Steger, C. (2019). A camera model for cameras with hypercentric lenses and some example applications. Machine vision and applications, 30 (6), 1013–1028. doi:10.1007/s00138-019-01032-w
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Weinmann, M.; Weinmann, M. (2019). Urban Scene Labeling Based on Multi-Modal Data Acquired from Aerial Sensor Platforms. 2019 Joint Urban Remote Sensing Event (JURSE), Vannes, France, France, 22 - 24 Mai 2019, 1–4, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/JURSE.2019.8809035
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Weinmann, M.; Weinmann, M. (2019). Fusion of hyperspectral, multispectral, color and 3D point cloud information for the semantic interpretation of urban environments. ISPRS Geospatial Week 2019, 10-14 June 2019, Enschede, The Netherlands, 1899–1906, ISPRS. doi:10.5194/isprs-archives-XLII-2-W13-1899-2019
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Wiegner, M.; Mattis, I.; Pattantyús-Ábrahám, M.; Bravo-Aranda, J. A.; Poltera, Y.; Haefele, A.; Hervo, M.; Görsdorf, U.; Leinweber, R.; Gasteiger, J.; Haeffelin, M.; Wagner, F.; Cermak, J.; Komínková, K.; Brettle, M.; Münkel, C.; Pönitz, K. (2019). Aerosol backscatter profiles from ceilometers: validation of water vapor correction in the framework of CeiLinEx2015. Atmospheric measurement techniques, 12 (1), 471–490. doi:10.5194/amt-12-471-2019
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Woollam, J.; Rietbrock, A.; Hinz, S.; Leitloff, J. (2019). HEX: Hyperbolic Event eXtractor, a seismic phase association algorithm for regions of intense seismicity. AGU Fall Meeting 2019, San Francisco, 9 – 13 December 2019.
2018
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Andersen, H.; Cermak, J. (2018). First fully diurnal fog and low cloud satellite detection reveals life cycle in the Namib. Atmospheric measurement techniques, 11 (10), 5461–5470. doi:10.5194/amt-11-5461-2018
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Bayram, B.; Demir, N.; Akpinar, B.; Oy, S.; Erdem, F.; Vögtle, T.; Seker, D. Z. (2018). Effect of different segmentation methods using optical satellite imagery to estimate fuzzy clustering parameters for Sentinel-1A SAR images. The international archives of photogrammetry, remote sensing and spatial information sciences, 42 (1), 39–43. doi:10.5194/isprs-archives-XLII-1-39-2018
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Boldt, M.; Thiele, A.; Schulz, K.; Hinz, S. (2018). On the categorization of high activity objects using differential attribute profiles. The international archives of photogrammetry, remote sensing and spatial information sciences, 42 (1), 59–64. doi:10.5194/isprs-archives-XLII-1-59-2018
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Boldt, M.; Thiele, A.; Schulz, K.; Hinz, S. (2018). On the classification of high activity objects. 12th European Conference on Synthetic Aperture Radar, EUSAR 2018; Eurogress AachenAachen; Germany; 4 June 2018 through 7 June 2018, 131–136, VDE Verlag.
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Bradley, P. E.; Keller, S.; Weinmann, M. (2018). Unsupervised Feature Selection Based on Ultrametricity and Sparse Training Data: A Case Study for the Classification of High-Dimensional Hyperspectral Data. Remote sensing, 10 (10), Art.Nr.: 1564. doi:10.3390/rs10101564
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Braun, A.; Stötzer, J.; Kubisch, S.; Keller, S. (2018). Critical Infrastructure Analysis (CRITIS) in Developing Regions – Designing an Approach to Analyse Peripheral Remoteness, Risks of Accessibility Loss, and Isolation due to Road Network Insufficiencies in Chile. GI-Forum, 6 (2), 302 - 321. doi:10.1553/giscience2018_02_s302
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Cermak, J. (2018). Fog and Low Cloud Frequency and Properties from Active-Sensor Satellite Data. Remote sensing, 10 (8), 1209. doi:10.3390/rs10081209
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Chen, K.; Fu, K.; Sun, X.; Weinmann, M.; Hinz, S.; Jutzi, B.; Weinmann, M. (2018). DEEP SEMANTIC SEGMENTATION OF AERIAL IMAGERY BASED ON MULTI-MODAL DATA. International Geoscience and Remote Sensing Symposium, Observing, Understanding and Forecasting the Dynamics of Our Planet (IGARSS 2018), Valencia, E, July 22-17, 2018, Institute of Electrical and Electronics Engineers (IEEE).
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Chen, K.; Weinmann, M.; Gao, X.; Yan, M.; Hinz, S.; Jutzi, B. (2018). Residual Shuffling Convolutional Neural Networks for Deep Semantic Image Segmentation Using Multi-Modal Data. 2018 ISPRS TC II Mid-term Symposium "Towards Photogrammetry 2020"; Riva del Garda; Italy, June 4-7, 2018. Ed.: T. Fuse, 65–72, Copernicus Publications. doi:10.5194/isprs-annals-IV-2-65-2018
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Chen, K.; Weinmann, M.; Sun, X.; Yan, M.; Hinz, S.; Jutzi, B.; Weinmann, M. (2018). SEMANTIC SEGMENTATION OF AERIAL IMAGERY VIA MULTI-SCALE SHUFFLING CONVOLUTIONAL NEURAL NETWORKS WITH DEEP SUPERVISION. ISPRS annals, IV-1, 29–36. doi:10.5194/isprs-annals-IV-1-29-2018
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Follmann, P.; Böttger, T.; Härtinger, P.; König, R.; Ulrich, M. (2018). MVTec D2S: Densely Segmented Supermarket Dataset. Computer Vision – ECCV 2018. Ed.: V. Ferrari, 581–597, Springer. doi:10.1007/978-3-030-01249-6_35
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Fuchs, J.; Cermak, J.; Andersen, H. (2018). Building a cloud in the southeast Atlantic: understanding low-cloud controls based on satellite observations with machine learning. Atmospheric chemistry and physics, 18 (22), 16537–16552. doi:10.5194/acp-18-16537-2018
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Gabriel, R.; Keller, S.; Matthes, J.; Waibel, P.; Keller, H. B.; Hinz, S. (2018). Infrared measurements and estimation of temperature in the restrictive scope of an industrial cement plant. 2018 ISPRS Technical Commission I Midterm Symposium on Innovative Sensing - From Sensors to Methods and Applications; Karlsruhe; Germany; 10 October 2018 through 12 October 2018, 53–60, Curran. doi:10.5194/isprs-annals-IV-1-53-2018
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Giovanella, A.; Bradley, P. E.; Wursthorn, S. (2018). Detection and evaluation of topological consistency in CityGML datasets. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, TC IV Mid-Term Symposium on 3D Spatial Information Science - The Engine of Change; Delft; NL, October 1-5, 2018, 59–66, Copernicus Publications. doi:10.5194/isprs-annals-IV-4-59-2018
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Grinberg, M.; Ruf, B.; Monka, S.; Kollman, M.; Buller, A.; Tchouchenkov, I. (2018). Embedded Stereokamera-basierte reaktive Kollisionsvermeidung für UAVs Embedded stereo vision based reactive collision avoidance for UAVs. Forum Bildverarbeitung 2018. Hrsg.: T. Längle, P. L. Fernando, M. Heizmann, 277–290, KIT Scientific Publishing. doi:10.5445/IR/1000088327
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Grudzielanek, A. M.; Cermak, J. (2018). Temporal Patterns and Vertical Temperature Gradients in Micro-Scale Drainage Flow Observed Using Thermal Imaging. Atmosphere, 9 (12), Article: 498. doi:10.3390/atmos9120498
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Heublein, M.; Alshawaf, F.; Erdnüß, B.; Zhu, X. X.; Hinz, S. (2018). Compressive sensing reconstruction of 3D wet refractivity based on GNSS and InSAR observations. Journal of geodesy, 1–21. doi:10.1007/s00190-018-1152-0
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Hübner, P.; Weinmann, M.; Hillemann, M.; Jutzi, B.; Wursthorn, S. (2018). Combining independent visualization and tracking systems for augmented reality. 2018 ISPRS TC II Mid-term Symposium “Towards Photogrammetry 2020”, 455–462, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLII-2-455-2018
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Hübner, P.; Weinmann, M.; Wursthorn, S. (2018). Marker-based localization of the Microsoft HoloLens in building models. ISPRS TC I Mid-term Symposium “Innovative Sensing – From Sensors to Methods and Applications", 195–202, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLII-1-195-2018
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Ilehag, R.; Bulatov, D.; Helmholz, P.; Belton, D. (2018). Classification and representation of commonly used roofing material using multisensorial aerial data. The international archives of photogrammetry, remote sensing and spatial information sciences, 42 (1), 217–224. doi:10.5194/isprs-archives-XLII-1-217-2018
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Jutzi, B.; Weinmann, M.; Hinz, S. (2018). PREFACE. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-1, 1–3. doi:10.5194/isprs-archives-XLII-1-1-2018
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Jutzi, B.; Weinmann, M.; Hinz, S. (2018). PREFACE. ISPRS annals, IV-1, 1–3. doi:10.5194/isprs-annals-IV-1-1-2018
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Keller, S.; Maier, P.; Riese, F.; Norra, S.; Holbach, A.; Börsig, N.; Wilhelms, A.; Moldaenke, C.; Zaake, A.; Hinz, S. (2018). Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity. International journal of environmental research and public health, 15 (9), 1881/1–15. doi:10.3390/ijerph15091881
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Keller, S.; Riese, F. M.; Allroggen, N.; Jackisch, C.; Hinz, S. (2018). Modeling Subsurface Soil Moisture Based on Hyperspectral Data : First Results of a Multilateral Field Campaign. Photogrammetrie, Fernerkundung, Geoinformatik, Kartographie 2018 (PFGK18) : Beiträge der 37. Wissenschaftlich-Technische Jahrestagung der DGPF e.V., 5. Münchner GI-Runde Runder Tisch GIS e.V. und des 66. Deutscher Kartographie Kongress der DGfK e.V., München, Deutschland, 7. - 9. März 2018. Hrsg.: T. P. Kersten, 34–48, Deutsche Gesellschaft für Photogrammetrie.
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Keller, S.; Riese, F. M.; Stötzer, J.; Maier, P. M.; Hinz, S. (2018). Developing a machine learning framework for estimating soil moisture with VNIR hyperspectral data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences - Symposium “Innovative Sensing – From Sensors to Methods and Applications”, Karlsruhe, Germany, 10–12 October 2018. Volume: IV-1, 101–108, ISPRS. doi:10.5194/isprs-annals-IV-1-101-2018
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Kern, J.; Schenk, A.; Hinz, S. (2018). Radiometric Calibration of a UAV-Mounted Hyperspectral Snapshot Camera with Focus on Uniform Spectral Sampling. 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2018), Amsterdam, NL, September 23-26, 2018, Article No.8747027, IEEE Computer Society. doi:10.1109/WHISPERS.2018.8747027
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Kim, M.; Lee, J.; Han, D.; Shin, M.; Im, J.; Lee, J.; Quackenbush, L. J.; Gu, Z. (2018). Convolutional Neural Network-Based Land Cover Classification Using 2-D Spectral Reflectance Curve Graphs With Multitemporal Satellite Imagery. IEEE journal of selected topics in applied earth observations and remote sensing, 11 (12), 4604–4617. doi:10.1109/JSTARS.2018.2880783
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Kim, M.; Lee, J.; Im, J. (2018). Deep learning-based monitoring of overshooting cloud tops from geostationary satellite data. GIScience and remote sensing, 55 (5), 763–792. doi:10.1080/15481603.2018.1457201
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Kuny, S.; Ihrig, R.; Boldt, M.; Thiele, A. (2018). Study on phenological changes in TerraSAR-X time series. 12th European Conference on Synthetic Aperture Radar, EUSAR 2018; Eurogress AachenAachen; Germany; 4 June 2018 through 7 June 2018, 55–58, VDE Verlag.
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Leitloff, J.; Riese, F. M. (2018). Examples for CNN training and classification on Sentinel-2 data. doi:10.5281/zenodo.3268451
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Maier, P. M.; Hinz, S.; Keller, S. (2018). Estimation of Chlorophyll a, Diatoms and Green Algae Based on Hyperspectral Data with Machine Learning Approaches. Photogrammetrie, Fernerkundung, Geoinformatik, Kartographie 2018 (PFGK18) : Beiträge der 37. Wissenschaftlich-Technische Jahrestagung der DGPF e.V., 5. Münchner GI-Runde Runder Tisch GIS e.V. und des 66. Deutscher Kartographie Kongress der DGfK e.V., München, Deutschland, 7. - 10. März 2018. Hrsg.: T. P. Kersten, 49–57, Deutsche Gesellschaft für Photogrammetrie.
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Maier, P. M.; Keller, S. (2018). Machine learning regression on hyperspectral data to estimate multiple water parameters.
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Mandlburger, G.; Jutzi, B. (2018). FEASIBILITY INVESTIGATION ON SINGLE PHOTON LIDAR BASED WATER SURFACE MAPPING. ISPRS annals, IV-1, 109–116. doi:10.5194/isprs-annals-IV-1-109-2018
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Mueller, M.; Metzger, A.; Jutzi, B. (2018). CNN-Based Initial Localization Improved by Data Augmentation. ISPRS TC I Mid-term Symposium “Innovative Sensing – From Sensors to Methods and Applications”, 10–12 October 2018, Karlsruhe, Germany, 117–124, ISPRS. doi:10.5194/isprs-annals-IV-1-117-2018
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Mueller, M. S.; Jutzi, B. (2018). UAS Navigation with SqueezePoseNet—Accuracy Boosting for Pose Regression by Data Augmentation. Drones, 2 (1), 7. doi:10.3390/drones2010007
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Müller, M.; Stüker, S.; Waibel, A. (2018). Neural language codes for multilingual acoustic models. 19th Annual Conference of the International Speech Communication, INTERSPEECH 2018; Hyderabad International Convention Centre (HICC)Hyderabad; India; 2 September 2018 through 6 September 2018. Ed.: C. C. Sekhar, 2419–2423, ISCA. doi:10.21437/Interspeech.2018-1241
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Müller, T.; Erdnüß, B. (2018). Stochastische Mustererkennung zur Bildsegmentierung = Stochastic pattern recognition for image segmentation. Forum Bildverarbeitung 2018. Hrsg.: T. Längle, P. L. Fernando, M. Heizmann, 173–184, KIT Scientific Publishing. doi:10.5445/IR/1000088266
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Niessner, R.; Schilling, H.; Hinz, S.; Jutzi, B. (2018). Klassifikation von Fahrzeugen aus RGB- und LiDAR-Daten mit Convolutional Neural Networks. 38. Wissenschaftlich-Technische Jahrestagung der DGPF und PFGK18 Tagung, München, 7-9. März 2018. Hrsg.: T.P. Kersten, 767–777, DGPF.
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Nilo, S. T.; Romano, F.; Cermak, J.; Cimini, D.; Ricciardelli, E.; Cersosimo, A.; Paola, F. D.; Gallucci, D.; Gentile, S.; Geraldi, E.; Larosa, S.; Ripepi, E.; Viggiano, M. (2018). Fog Detection Based on Meteosat Second Generation-Spinning Enhanced Visible and InfraRed Imager High Resolution Visible Channel. Remote sensing, 10 (4), Art.Nr. 541. doi:10.3390/rs10040541
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Riese, F. M.; Keller, S. (2018). Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22nd - 27th July, 2018, 6151–6154, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS.2018.8517812
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Riese, F. M.; Keller, S. (2018, April 24). Hyperspectral benchmark dataset on soil moisture. doi:10.5281/zenodo.1227837
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Riese, F. M.; Keller, S. (2018). Fusion of hyperspectral and ground penetrating radar data to estimate soil moisture. 9th Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (Whispers 2018), Amsterdam, NL, September 23-26, 2018, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WHISPERS.2018.8747076
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Ruf, B.; Monka, S.; Kollmann, M.; Grinberg, M. (2018). Real-Time On-Board Obstacle Avoidance for UAVs based on Embedded Stereo Vision. The international archives of photogrammetry, remote sensing and spatial information sciences, XLII-1, 363–370. doi:10.5194/isprs-archives-XLII-1-363-2018
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Ruf, B.; Thiel, L.; Weinmann, M. (2018). Deep Cross-Domain Building Extraction for Selective Depth Estimation from Oblique Aerial Imagery. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-1, 125–132. doi:10.5194/isprs-annals-IV-1-125-2018
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Siegfarth, C.; Voegtle, T.; Fabinski, C. (2018). Comparison of two methods for 2D pose estimation of industrial workpieces in images - CNN vs. Classical image processing system. The international archives of photogrammetry, remote sensing and spatial information sciences, 42 (1), 401–405. doi:10.5194/isprs-archives-XLII-1-401-2018
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Stirnberg, R.; Cermak, J.; Andersen, H. (2018). An Analysis of Factors Influencing the Relationship between Satellite-Derived AOD and Ground-Level PM10. Remote sensing, 10 (9), Art.-Nr.: 1353/1–17. doi:10.3390/rs10091353
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Weinmann, M.; Maier, P. M.; Florath, J.; Weidner, U. (2018). Investigation on the potential of hyperspectral and Sentinel-2 data for land-cover / land-use classification. 2018 ISPRS Technical Commission I Midterm Symposium on Innovative Sensing - From Sensors to Methods and Applications; Karlsruhe; Germany; 10 October 2018 through 12 October 2018. Ed.: S. Hinz, 155–162, Curran. doi:10.5194/isprs-annals-IV-1-155-2018
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Weinmann, M.; Weidner, U. (2018). Erste Erfahrungen mit der Nutzung von Sentinel-2 Daten zur multispektralen und multitemporalen Analyse mit verschiedenen Klassifizierungsverfahren. Photogrammetrie - Fernerkundung - Geoinformatik - Kartographie - 2018 : 38. Wissenschaftlich-Technische Jahrestagung der DGPF e.V., 5. Münchner GI-Runde Runder Tisch GIS e.V., 66. Deutscher Kartographie Kongress der DGfK e.V. : 7.-9. März 2018 in München : Beiträge, 58–70, DGPF.
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Weinmann, M.; Blomley, R.; Weinmann, M.; Jutzi, B. (2018). Investigations on the potential of binary and multi-class classification for object extraction from airborne laser scanning point clouds. 38. Wissenschaftlich-Technische Jahrestagung der DGPF und PFGK18 Tagung, München, 7-9. März 2018. Hrsg.: T.P. Kersten, 408–421, DGPF.
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Weinmann, M.; Weidner, U. (2018). Land-Cover and Land-Use Classification Based on Multitemporal Sentinel-2 Data. IEEE International Geoscience & Remote Sensing Symposium : proceedings : July 22–27, 2018, Valencia, Spain, 4946–4949, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS.2018.8519301
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Weinmann, M.; Weinmann, M. (2018). Geospatial Computer Vision Based on Multi-Modal Data—How Valuable Is Shape Information for the Extraction of Semantic Information?. Remote sensing, 10 (1), 2. doi:10.3390/rs10010002
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Welte, A.; Hammer, H.; Thiele, A.; Hinz, S. (2018). Urban change detection in TanDEM-X interferograms. 12th European Conference on Synthetic Aperture Radar, EUSAR 2018; Eurogress AachenAachen; Germany; 4 June 2018 through 7 June 2018, 148–152, VDE Verlag.
2017
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Andersen, H.; Cermak, J.; Fuchs, J.; Knutti, R.; Lohmann, U. (2017). Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks. Atmospheric chemistry and physics, 17 (15), 9535–9546. doi:10.5194/acp-17-9535-2017
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Bartelsen, J.; Müller, T.; Ring, J.; Mück, K.; Brüstle, S.; Erdnüß, B.; Lutz, B.; Herbst, T. (2017). Video change detection for fixed wing UAVs. SPIE Security + Defence : Target and Background Signatures, Warsaw, Poland, 11th - 14th September 2017, Art.Nr. 104320K, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2278094
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Blomley, R.; Hovi, A.; Weinmann, M.; Hinz, S.; Korpela, I.; Jutzi, B. (2017). Tree species classification using within crown localization of waveform LiDAR attributes. ISPRS journal of photogrammetry and remote sensing, 133, 142–156. doi:10.1016/j.isprsjprs.2017.08.013
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Boldt, M.; Thiele, A.; Schulz, K.; Hinz, S. (2017). Change Classification in SAR Time Series : A Functional Approach. SPIE Remote Sensing : Earth Resources and Environmental Remote Sensing/GIS Applications VIII, Warsaw, Poland, 11th - 14th September 2017, Art.Nr. 1042802, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2277578
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Böttger, T.; Ulrich, M.; Steger, C. (2017). Subpixel-Precise Tracking of Rigid Objects in Real-Time. Image Analysis. Part 1. Ed.: P. Sharma, 54–65, Springer Verlag. doi:10.1007/978-3-319-59126-1_5
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Bradley, P. E. (2017). Finding Ultrametricity in Data using Topology. Journal of classification, 34 (1), 76–84. doi:10.1007/s00357-017-9228-8
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Breunig, M.; Borrmann, A.; Rank, E.; Hinz, S.; Kolbe, T.; Schilcher, M.; Mundani, R.-P.; Jubierre, J. R.; Flurl, M.; Thomsen, A.; Donaubauer, A.; Ji, Y.; Urban, S.; Laun, S.; Vilgertshofer, S.; Willenborg, B.; Menninghaus, M.; Steuer, H.; Wursthorn, S.; Leitloff, J.; Al-Doori, M.; Mazroobsemnani, N. (2017). Collaborative multi-scale 3D city and infrastructure modeling and simulation. The international archives of photogrammetry, remote sensing and spatial information sciences, 42 (4W4), 341–352. doi:10.5194/isprs-archives-XLII-4-W4-341-2017
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CEDIM. (2017). CEDIM Research Report 2015-2016. (M. Kunz & A. Dittrich, Hrsg.), CEDIM. doi:10.5445/IR/1000069933
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Dittrich, A.; Weinmann, M.; Hinz, S. (2017). Analytical and numerical investigations on the accuracy and robustness of geometric features extracted from 3D point cloud data. ISPRS journal of photogrammetry and remote sensing, (126), 195–208. doi:10.1016/j.isprsjprs.2017.02.012
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Drost, B.; Ulrich, M.; Bergmann, P.; Härtinger, P.; Steger, C. (2017). Introducing MVTec ITODD — A Dataset for 3D Object Recognition in Industry. 2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2200–2208, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICCVW.2017.257
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Dubois, C.; Nascetti, A.; Thiele, A.; Crespi, M.; Hinz, S. (2017). SAR-SIFT for matching multiple SAR images and radargrammetry [SAR-SIFT für das Matching von Multiplen SAR Bildern und Radargrammetry]. PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 85 (3), 149–158. doi:10.1007/s41064-017-0019-y
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Erdnüß, B. (2017). Das baryzentrische Verhältnis als Invariante der projektiven Geometrie = The barycentric ratio as invariant of projective geometry. Technisches Messen, 84 (7-8), 479–492. doi:10.1515/teme-2017-0014
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Fuchs, J.; Cermak, J.; Andersen, H.; Hollmann, R.; Schwarz, K. (2017). On the Influence of Air Mass Origin on Low-Cloud Properties in the Southeast Atlantic. Journal of geophysical research / Atmospheres. doi:10.1002/2017JD027184
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Hillemann, M.; Jutzi, B. (2017). UCalMiCeL - Unified Intrinsic and Extrinsic Calibration of a Multi-Camera-System and a Laserscanner. 4th ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences - International Conference on Unmanned Aerial Vehicles in Geomatics, Bonn, Germany, 4.-7. September 2017. Ed.: C. Stachniss. Vol. IV-2/W3., 49–57, ISPRS. doi:10.5194/isprs-annals-IV-2-W3-17-2017
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Ilehag, R.; Schenk, A.; Hinz, S. (2017). Concept for classifying facade elements based on material, geometry and thermal radiation using multimodal UAV remote sensing. 4th ISPRS International Conference on Unmanned Aerial Vehicles in Geomatics, Bonn, Germany, 4th - 7th September 2017, 145–151, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLII-2-W6-145-2017
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