% % SPFormer: Self-Pooling Transformer for Few-Shot Hyperspectral Image Classification. % Version: 1.0 % Date : Dec. 2023 % % This demo implements the SPFormer model for hyperspectral image classification. % %
% % -------------------------------------- % Note: Required % -------------------------------------- % 1. python==3.6 % 2. torch==1.10.2 % 3. cuda==11.1.1 % -------------------------------------- % Cite: % -------------------------------------- % % [1] Z. Li, Z. Xue, Q. Xu, L. Zhang, T. Zhu and M. Zhang, "SPFormer: Self-Pooling Transformer for Few-Shot Hyperspectral Image Classification," in IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-19, 2024, Art no. 5502019. % % -------------------------------------- % Copyright & Disclaimer % -------------------------------------- % % The programs contained in this package are granted free of charge for % research and education purposes only. % % Copyright (c) 2022 by Zhaohui Xue % zhaohui.xue@hhu.edu.cn % -------------------------------------- % For full package: % -------------------------------------- % https://sites.google.com/site/zhaohuixuers/