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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLIII-B2-2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-383-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-383-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
12 Aug 2020
| 12 Aug 2020
LONG-SHORT SKIP CONNECTIONS IN DEEP NEURAL NETWORKS FOR DSM REFINEMENT
K. Bittner
Remote Sensing Technology Institute, German Aerospace Center (DLR), Wessling, Germany
L. Liebel
Computer Vision Research Group, Chair of Remote Sensing Technology (LMF), Technical University of Munich (TUM), Munich, Germany
M. Körner
Computer Vision Research Group, Chair of Remote Sensing Technology (LMF), Technical University of Munich (TUM), Munich, Germany
P. Reinartz
Remote Sensing Technology Institute, German Aerospace Center (DLR), Wessling, Germany
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ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 95–101, https://doi.org/10.5194/isprs-annals-IV-2-W7-95-2019, https://doi.org/10.5194/isprs-annals-IV-2-W7-95-2019, 2019
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C. Kempf, J. Tian, F. Kurz, P. d’Angelo, and P. Reinartz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 43–50, https://doi.org/10.5194/isprs-archives-XLII-2-W13-43-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-43-2019, 2019
S. Azimi, E. Vig, F. Kurz, and P. Reinartz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 19–23, https://doi.org/10.5194/isprs-archives-XLII-1-19-2018, https://doi.org/10.5194/isprs-archives-XLII-1-19-2018, 2018
F. Kurz, D. Waigand, P. Pekezou-Fouopi, E. Vig, C. Henry, N. Merkle, D. Rosenbaum, V. Gstaiger, S. Azimi, S. Auer, P. Reinartz, and S. Knake-Langhorst
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 251–256, https://doi.org/10.5194/isprs-archives-XLII-1-251-2018, https://doi.org/10.5194/isprs-archives-XLII-1-251-2018, 2018
K. Bittner, P. d’Angelo, M. Körner, and P. Reinartz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 103–108, https://doi.org/10.5194/isprs-archives-XLII-2-103-2018, https://doi.org/10.5194/isprs-archives-XLII-2-103-2018, 2018
M. Schmitt, L. H. Hughes, M. Körner, and X. X. Zhu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1045–1051, https://doi.org/10.5194/isprs-archives-XLII-2-1045-2018, https://doi.org/10.5194/isprs-archives-XLII-2-1045-2018, 2018
Y. Xia, J. Tian, P. d’Angelo, and P. Reinartz
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 303–309, https://doi.org/10.5194/isprs-annals-IV-2-303-2018, https://doi.org/10.5194/isprs-annals-IV-2-303-2018, 2018
Ekaterina Chuprikova, Lukas Liebel, and Liqiu Meng
Proc. Int. Cartogr. Assoc., 1, 23, https://doi.org/10.5194/ica-proc-1-23-2018, https://doi.org/10.5194/ica-proc-1-23-2018, 2018
J. Mu, S. Cui, and P. Reinartz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 159–165, https://doi.org/10.5194/isprs-archives-XLII-1-W1-159-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-159-2017, 2017
D. Cerra, D. Traganos, P. Gege, and P. Reinartz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 279–282, https://doi.org/10.5194/isprs-archives-XLII-1-W1-279-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-279-2017, 2017
D. Traganos, D. Cerra, and P. Reinartz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 283–287, https://doi.org/10.5194/isprs-archives-XLII-1-W1-283-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-283-2017, 2017
K. Bittner, S. Cui, and P. Reinartz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 481–486, https://doi.org/10.5194/isprs-archives-XLII-1-W1-481-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-481-2017, 2017
M. Rußwurm and M. Körner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 551–558, https://doi.org/10.5194/isprs-archives-XLII-1-W1-551-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-551-2017, 2017
T. Partovi, F. Fraundorfer, S. Azimi, D. Marmanis, and P. Reinartz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 653–657, https://doi.org/10.5194/isprs-archives-XLII-1-W1-653-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-653-2017, 2017
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 883–890, https://doi.org/10.5194/isprs-archives-XLI-B3-883-2016, https://doi.org/10.5194/isprs-archives-XLI-B3-883-2016, 2016
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