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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLIII-B3-2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-767-2020
© 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-B3-2020-767-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
21 Aug 2020
| 21 Aug 2020
AUTOMATICALLY GENERATED TRAINING DATA FOR LAND COVER CLASSIFICATION WITH CNNS USING SENTINEL-2 IMAGES
M. Voelsen
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
J. Bostelmann
German Land Survey Office of Lower Saxony (LGLN), Hannover, Germany
A. Maas
German Land Survey Office of Lower Saxony (LGLN), Hannover, Germany
F. Rottensteiner
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
C. Heipke
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1355–1362, https://doi.org/10.5194/isprs-archives-XLII-3-1355-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1355-2018, 2018
Christian Kruse, Franz Rottensteiner, Thorsten Hoberg, Marcel Ziems, Julia Rebke, and Christian Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 127–134, https://doi.org/10.5194/isprs-annals-IV-3-127-2018, https://doi.org/10.5194/isprs-annals-IV-3-127-2018, 2018
Chun Yang, Franz Rottensteiner, and Christian Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 251–258, https://doi.org/10.5194/isprs-annals-IV-3-251-2018, https://doi.org/10.5194/isprs-annals-IV-3-251-2018, 2018
J. Unger, F. Rottensteiner, and C. Heipke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 385–392, https://doi.org/10.5194/isprs-archives-XLII-2-W6-385-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-385-2017, 2017
M. Coenen, F. Rottensteiner, and C. Heipke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 505–512, https://doi.org/10.5194/isprs-archives-XLII-1-W1-505-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-505-2017, 2017
Christian Heipke, Karsten Jacobsen, Uwe Stilla, Franz Rottensteiner, Alper Yilmaz, Michael Ying Yang, Jan Skaloud, and Ismael Colomina
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1-W1, 1–2, https://doi.org/10.5194/isprs-annals-IV-1-W1-1-2017, https://doi.org/10.5194/isprs-annals-IV-1-W1-1-2017, 2017
C. Heipke, K. Jacobsen, U. Stilla, F. Rottensteiner, A. Yilmaz, M. Ying Yang, J. Skaloud, and I. Colomina
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 1–2, https://doi.org/10.5194/isprs-archives-XLII-1-W1-1-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-1-2017, 2017
A. Maas, M. Alrajhi, A. Alobeid, and C. Heipke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 11–16, https://doi.org/10.5194/isprs-archives-XLII-1-W1-11-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-11-2017, 2017
A. Maas, F. Rottensteiner, and C. Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1-W1, 215–222, https://doi.org/10.5194/isprs-annals-IV-1-W1-215-2017, https://doi.org/10.5194/isprs-annals-IV-1-W1-215-2017, 2017
K. Vogt, A. Paul, J. Ostermann, F. Rottensteiner, and C. Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1-W1, 229–236, https://doi.org/10.5194/isprs-annals-IV-1-W1-229-2017, https://doi.org/10.5194/isprs-annals-IV-1-W1-229-2017, 2017
C. Heipke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5-W7, 543–543, https://doi.org/10.5194/isprs-archives-XL-5-W7-543-2016, https://doi.org/10.5194/isprs-archives-XL-5-W7-543-2016, 2016
The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.
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