This example implements the paper in review [A Fast Dynamic Graph Convolutional Network and CNN Parallel Network for Hyperspectral Image Classification]

If you want to run this code, just put your data in the Datasets folder and change a few paths.

• path 1: main.py:path-config.
• path 2: data_reader.py: add or change to your data path, just in Folder path.
• config.yaml: your Folder path and dataset name, your weight and result store path.

then:

python main.py

This project is implemented with Pytorch and has been tested on version

• Pytorch 1.7,
• numpy 1.21.4
• matplotlib 3.3.3
• scikit-learn 0.23.2

Please kindly cite the papers A Fast Dynamic Graph Convolutional Network and CNN Parallel Network for Hyperspectral Image Classification if this code is useful and helpful for your research.

@ARTICLE{9785802,  author={Liu, Quanwei and Dong, Yanni and Zhang, Yuxiang and Luo, Hui},  journal={IEEE Transactions on Geoscience and Remote Sensing},   title={A Fast Dynamic Graph Convolutional Network and CNN Parallel Network for Hyperspectral Image Classification},   year={2022},  volume={60},  number={},  pages={1-15},  doi={10.1109/TGRS.2022.3179419}}