BENCHMARKING DEEP LEARNING FRAMEWORKS FOR THE CLASSIFICATION OF  VERY HIGH RESOLUTION SATELLITE MULTISPECTRAL DATA

Papadomanolaki, M.; Vakalopoulou, M.; Zagoruyko, S.; Karantzalos, K.

doi:https://doi.org/10.5194/isprs-annals-III-7-83-2016

Articles | Volume III-7

https://doi.org/10.5194/isprs-annals-III-7-83-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/isprs-annals-III-7-83-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume III-7

07 Jun 2016

| 07 Jun 2016

BENCHMARKING DEEP LEARNING FRAMEWORKS FOR THE CLASSIFICATION OF VERY HIGH RESOLUTION SATELLITE MULTISPECTRAL DATA

M. Papadomanolaki, M. Vakalopoulou, S. Zagoruyko, and K. Karantzalos

Related authors

URBAN CHANGE DETECTION BASED ON SEMANTIC SEGMENTATION AND FULLY CONVOLUTIONAL LSTM NETWORKS

M. Papadomanolaki, M. Vakalopoulou, and K. Karantzalos

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 541–547, https://doi.org/10.5194/isprs-annals-V-2-2020-541-2020,https://doi.org/10.5194/isprs-annals-V-2-2020-541-2020, 2020

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.

Useful Links

Useful External Links

Our Contact

ISPRS
c/o
Leibniz University Hannover
Institute of Photogrammetry and GeoInformation
Nienburger Str. 1
D-30167 Hannover
GERMANY
Email: isprs-sg@isprs.org