LICENSE_DeepHyperX.txt

# License information:
The following files in this repository: 

data_dataset.py, 
data_loader.py, 
main_test.py, 
main_train.py, 
models.py, trainer.py, 
utils.py                    

are based on the code in library: https://github.com/nshaud/DeepHyperX
for paper
N. Audebert, B. Le Saux and S. Lefevre, "Deep Learning for Classification of Hyperspectral Data: A Comparative Review,"
in IEEE Geoscience and Remote Sensing Magazine, vol. 7, no. 2, pp. 159-173, June 2019.

The code is used for RESEARCH AND NON COMMERCIAL PURPOSES under the licence:
https://github.com/nshaud/DeepHyperX/blob/master/License

# Original licence from https://github.com/nshaud/DeepHyperX/blob/master/License:	

# License information

Code for the DeepHyperX toolbox is dual licensed depending on applications, research or commercial.

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## COMMERCIAL PURPOSES

Please contact the ONERA [www.onera.fr/en/contact-us](www.onera.fr/en/contact-us) for additional information or directly the authors Nicolas Audebert or Bertrand Le Saux.

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## RESEARCH AND NON COMMERCIAL PURPOSES

#### Code license

For research and non commercial purposes, all the code and documentation is released under the GPLv3 license:

Copyright (c) 2018 ONERA and IRISA, Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre.

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.

PLEASE ACKNOWLEDGE THE ORIGINAL AUTHORS AND PUBLICATION ACCORDING TO THE REPOSITORY github.com/nshaud/DeepHyperx OR IF NOT AVAILABLE:
Nicolas Audebert, Bertrand Le Saux and Sébastien Lefèvre
"Deep Learning for Classification of Hyperspectral Data: A comparative review",
IEEE Geosciences and Remote Sensing Magazine, 2019.