code for paper：A high-resolution feature network image-level classification method for hyperspectral image， Acta Geodaetica et Cartographica Sinica (AGCS)
If the code is helpful to you, please give a star or fork and cite the paper. Thanks!
os argparse time numpy torch datetime sklearn
We provide a demo of the Salinas hyperspectral data by run the file of train_fastnet_vote_SA.py. The data is put in the realease, you need to download it and put it into the HSI_data file. If you want to run the code in your own data, you can accordingly change the input and tune the parameters. Please refer to the paper for more details.
Copyright (C) 2022 Yifan Sun
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, version 3 of the License.
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.
[1] @article{WangSCJDZLMTWLX19, title={Deep High-Resolution Representation Learning for Visual Recognition}, author={Jingdong Wang and Ke Sun and Tianheng Cheng and Borui Jiang and Chaorui Deng and Yang Zhao and Dong Liu and Yadong Mu and Mingkui Tan and Xinggang Wang and Wenyu Liu and Bin Xiao}, journal={TPAMI}, year={2019} }