README.md

Extreme-Xception-Net-for-HSIC

Reference

This code is used for our research paper:

U. Ghous, et.al., "(2+1)D Extreme Xception Net for Hyperspectral Image Classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024.

Please cite: @ARTICLE{10423094, author={Ghous, Usman and Sarfraz, Muhammad Shahzad and Ahmad, Muhammad and Li, Chenyu and Hong, Danfeng}, journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, title={(2+1)D Extreme Xception Net for Hyperspectral Image Classification}, year={2024}, volume={}, number={}, pages={1-14}, doi={10.1109/JSTARS.2024.3362936}}

(2+1)D Extreme Xception Net (Proposed)

2D CNN

2D Inception Net

3D Inception Net

2D Xception Net

3D CNN

Hybrid Net

LeNet

ZFnet

AlexNet

Requirements

This tool is compatible with Python 2.7 and Python 3.5+ and executed over Colab.

Hyperspectral datasets

Several public hyperspectral datasets are available on the EHU. Users can download those beforehand.

An example dataset folder has the following structure:

Datasets
├── IndianPines
│   ├── Indian_pines_corrected.mat
│   ├── Indian_pines_gt.mat
├── University of Houston
│   ├── UH.mat
│   └── UG_gt.mat

RESEARCH AND NON-COMMERCIAL PURPOSES