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Readme.txt
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Readme.txt
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%
% S3Net: Spectral–Spatial Siamese Network for Few-Shot Hyperspectral Image Classification.
%
% This demo shows the S3Net model for hyperspectral image classification.
%
% main.py ....... A main script executing experiments upon IP, PU, and HU data sets.
% data_read.py ....... A script implementing various data manipulation functions.
% Function.py ....... A script implementing the precision calculation, claasificaiton map drawing, and etc.
% model.pyd ....... A script implementing the S3Net model.
% loss_function.py ....... A script implementing some loss functions.
% Final_Experiment.csv ...... A csv saving the accuracy information after training
%
% /Dataset ............... The folder including data sets, we put in Salinas in it.
% /model_results ............... The folder containing the model parameters after training.
%
% --------------------------------------
% Note: Required core python libraries
% --------------------------------------
% 1. python 3.7
% 2. pytorch 1.7.1
% 3. torchvision 0.8.2
% --------------------------------------
% Cite:
% --------------------------------------
%
% [1] Z. Xue, Y. Zhou and P. Du, "S3Net: Spectral-Spatial Siamese Network for Few-Shot Hyperspectral Image Classification," in IEEE Transactions on Geoscience and Remote Sensing, 2022, doi: 10.1109/TGRS.2022.3181501.
% --------------------------------------
% Copyright & Disclaimer
% --------------------------------------
%
% The programs contained in this package are granted free of charge for
% research and education purposes only.
%
% Copyright (c) 2021 by Zhaohui Xue & Yiyang Zhou
% zhaohui.xue@hhu.edu.cn & hohai_zyy@163.com
% --------------------------------------
% For full package:
% --------------------------------------
% https://sites.google.com/site/zhaohuixuers/