This example implements the paper in review [Weighted Feature Fusion of Convolutional Neural Network and Graph Attention 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: datasets: Please put the corresponding hyperspectral data there.
• path 2: loadData/data_reader.py: change datasets path.

python main.py -pc -pdi -sr

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 Weighted Feature Fusion of Convolutional Neural Network and Graph Attention Network for Hyperspectral Image Classification if this code is useful and helpful for your research.

@ARTICLE{9693311,
  author={Dong, Yanni and Liu, Quanwei and Du, Bo and Zhang, Liangpei},
  journal={IEEE Transactions on Image Processing}, 
  title={Weighted Feature Fusion of Convolutional Neural Network and Graph Attention Network for Hyperspectral Image Classification}, 
  year={2022},
  volume={31},
  number={},
  pages={1559-1572},
  doi={10.1109/TIP.2022.3144017}}