-
1
-
-
85044377671
-
Learning diverse image colorization
-
Honolulu, HI, USA
-
Deshpande, A., Lu, J., Yeh, M.-C., Chong, M. J. And Forsyth, D., 2017. Learning diverse image colorization. In: Proc. CVPR, Honolulu, HI, USA, pp. 6837-6845.
-
(2017)
Proc. CVPR
, pp. 6837-6845
-
-
Deshpande, A.1
Lu, J.2
Yeh, M.-C.3
Chong, M.J.4
Forsyth, D.5
-
2
-
-
84859427372
-
Sentinel-2: Esa's optical high-resolution mission for gmes operational services
-
Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., Hoersch, B., Isola, C., Laberinti, P., Martimort, P. et al., 2012. Sentinel-2: ESA's optical high-resolution mission for GMES operational services. Remote sensing of Environment 120, pp. 25-36.
-
(2012)
Remote Sensing of Environment
, vol.120
, pp. 25-36
-
-
Drusch, M.1
Del Bello, U.2
Carlier, S.3
Colin, O.4
Fernandez, V.5
Gascon, F.6
Hoersch, B.7
Isola, C.8
Laberinti, P.9
Martimort, P.10
-
3
-
-
85016482816
-
-
European Space Agency, (Accessed July 30, 2018)
-
European Space Agency, 2015. Sentinels: Space for Copernicus. http://esamultimedia. esa. int/multimedia/ publications/sentinels-family/. (Accessed July 30, 2018).
-
(2015)
Sentinels: Space for Copernicus
-
-
-
4
-
-
85021781951
-
Google earth engine: Planetary-scale geospatial analysis for everyone
-
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D. And Moore, R., 2017. Google earth engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment 202, pp. 18-27.
-
(2017)
Remote Sensing of Environment
, vol.202
, pp. 18-27
-
-
Gorelick, N.1
Hancher, M.2
Dixon, M.3
Ilyushchenko, S.4
Thau, D.5
Moore, R.6
-
5
-
-
85056354296
-
A conditional generative adversarial network to fuse sar and multispectral optical data for cloud removal from sentinel-2 images
-
Valencia, Spain. in press
-
Grohnfeldt, C., Schmitt, M. And Zhu, X., 2018. A conditional generative adversarial network to fuse SAR and multispectral optical data for cloud removal from Sentinel-2 images. In: Proc. IGARSS, Valencia, Spain. in press.
-
(2018)
Proc. IGARSS
-
-
Grohnfeldt, C.1
Schmitt, M.2
Zhu, X.3
-
6
-
-
85043467411
-
Identifying corresponding patches in sar and optical images with a pseudo-siamese cnn
-
Hughes, L. H., Schmitt, M., Mou, L., Wang, Y. And Zhu, X. X., 2018. Identifying corresponding patches in SAR and optical images with a pseudo-siamese CNN. IEEE Geoscience and Remote Sensing Letters 15(5), pp. 784-788.
-
(2018)
IEEE Geoscience and Remote Sensing Letters
, vol.15
, Issue.5
, pp. 784-788
-
-
Hughes, L.H.1
Schmitt, M.2
Mou, L.3
Wang, Y.4
Zhu, X.X.5
-
7
-
-
85030759098
-
Imageto-image translation with conditional adversarial networks
-
Honolulu, HI, USA
-
Isola, P., Zhu, J.-Y., Zhou, T. And Efros, A. A., 2017. Imageto-image translation with conditional adversarial networks. In: Proc. CVPR, Honolulu, HI, USA, pp. 1125-1134.
-
(2017)
Proc. CVPR
, pp. 1125-1134
-
-
Isola, P.1
Zhu, J.-Y.2
Zhou, T.3
Efros, A.A.4
-
8
-
-
85050481064
-
Exploiting gan-based sar to optical image transcoding for improved classification via deep learning
-
Aachen, Germany
-
Ley, A., d'Hondt, O., Valade, S., Hänsch, R. And Hellwich, O., 2018. Exploiting GAN-based SAR to optical image transcoding for improved classification via deep learning. In: Proc. EUSAR, Aachen, Germany, pp. 396-401.
-
(2018)
Proc. EUSAR
, pp. 396-401
-
-
Ley, A.1
D'Hondt, O.2
Valade, S.3
Hänsch, R.4
Hellwich, O.5
-
9
-
-
85052975213
-
Artificial generation of big data for improving image classification: A generative adversarial network approach on sar data
-
Toulouse, France
-
Marmanis, D., Yao, W., Adam, F., Datcu, M., Reinartz, P., Schindler, K., Wegner, J. D. And Stilla, U., 2017. Artificial generation of big data for improving image classification: A generative adversarial network approach on SAR data. In: Proc. BiDS, Toulouse, France, pp. 293-296.
-
(2017)
Proc. BiDS
, pp. 293-296
-
-
Marmanis, D.1
Yao, W.2
Adam, F.3
Datcu, M.4
Reinartz, P.5
Schindler, K.6
Wegner, J.D.7
Stilla, U.8
-
10
-
-
85044761197
-
Exploring the potential of conditional adversarial networks for optical and sar image matching
-
in press
-
Merkle, N., Auer, S., Müller, R. And Reinartz, P., 2018. Exploring the potential of conditional adversarial networks for optical and SAR image matching. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. in press.
-
(2018)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
-
-
Merkle, N.1
Auer, S.2
Müller, R.3
Reinartz, P.4
-
11
-
-
85021174875
-
Exploiting deep matching and sar data for the geolocalization accuracy improvement of optical satellite images
-
Merkle, N., Wenjie, L., Auer, S., Müller, R. And Urtasun, R., 2017. Exploiting deep matching and SAR data for the geolocalization accuracy improvement of optical satellite images. Remote Sensing 9(9), pp. 586-603.
-
(2017)
Remote Sensing
, vol.9
, Issue.9
, pp. 586-603
-
-
Merkle, N.1
Wenjie, L.2
Auer, S.3
Müller, R.4
Urtasun, R.5
-
12
-
-
85007413470
-
Data fusion and remote sensing-an ever-growing relationship
-
Schmitt, M. And Zhu, X., 2016. Data fusion and remote sensing-an ever-growing relationship. IEEE Geosci. Remote Sens. Mag. 4(4), pp. 6-23.
-
(2016)
IEEE Geosci. Remote Sens. Mag.
, vol.4
, Issue.4
, pp. 6-23
-
-
Schmitt, M.1
Zhu, X.2
-
13
-
-
85048356423
-
Colorizing sentinel-1 sar images using a variational autoencoder conditioned on sentinel-2 imagery
-
Schmitt, M., Hughes, L. H., Körner, M. And Zhu, X. X., 2018. Colorizing Sentinel-1 SAR images using a variational autoencoder conditioned on Sentinel-2 imagery. In: Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., Vol. XLII-2, pp. 1045-1051.
-
(2018)
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.
, vol.XLII-2
, pp. 1045-1051
-
-
Schmitt, M.1
Hughes, L.H.2
Körner, M.3
Zhu, X.X.4
-
14
-
-
84937855061
-
Sentinel-1a product geolocation accuracy: Commissioning phase results
-
Schubert, A., Small, D., Miranda, N., Geudtner, D. And Meier, E., 2015. Sentinel-1a product geolocation accuracy: Commissioning phase results. Remote Sensing 7(7), pp. 9431-9449.
-
(2015)
Remote Sensing
, vol.7
, Issue.7
, pp. 9431-9449
-
-
Schubert, A.1
Small, D.2
Miranda, N.3
Geudtner, D.4
Meier, E.5
-
15
-
-
84863393480
-
Gmes sentinel-1 mission
-
Torres, R., Snoeij, P., Geudtner, D., Bibby, D., Davidson, M., Attema, E., Potin, P., Rommen, B., Floury, N., Brown, M. et al., 2012. GMES Sentinel-1 mission. Remote Sensing of Environment 120, pp. 9-24.
-
(2012)
Remote Sensing of Environment
, vol.120
, pp. 9-24
-
-
Torres, R.1
Snoeij, P.2
Geudtner, D.3
Bibby, D.4
Davidson, M.5
Attema, E.6
Potin, P.7
Rommen, B.8
Floury, N.9
Brown, M.10
-
18
-
-
84976384382
-
Deep learning for remote sensing data
-
Zhang, L., Zhang, L. And Du, B., 2016. Deep learning for remote sensing data. IEEE Geoscience and Remote Sensing Magazine 4(2), pp. 22-40.
-
(2016)
IEEE Geoscience and Remote Sensing Magazine
, vol.4
, Issue.2
, pp. 22-40
-
-
Zhang, L.1
Zhang, L.2
Du, B.3
-
19
-
-
85040367775
-
Deep learning in remote sensing: A comprehensive review and list of resources
-
Zhu, X. X., Tuia, D., Mou, L., Xia, G.-S., Zhang, L., Xu, F. And Fraundorfer, F., 2017. Deep learning in remote sensing: A comprehensive review and list of resources. IEEE Geoscience and Remote Sensing Magazine 5(4), pp. 8-36.
-
(2017)
IEEE Geoscience and Remote Sensing Magazine
, vol.5
, Issue.4
, pp. 8-36
-
-
Zhu, X.X.1
Tuia, D.2
Mou, L.3
Xia, G.-S.4
Zhang, L.5
Xu, F.6
Fraundorfer, F.7
|