PyTorch implementation of SS-MLP: A Novel Spectral-Spatial MLP Architecture for Hyperspectral Image Classification.
import torch
from SSMLP import SSMLP
model = SSMLP(num_classes=16, channels=200, patchsize=11)
model.eval()
print(model)
input = torch.randn(100, 200, 11, 11)
y = model(input)
print(y.size()) # (100, 16)
SS-MLP: A Novel Spectral-Spatial MLP Architecture for Hyperspectral Image Classification
Please cite our paper if you find it useful for your research.
@article{meng2021ss,
title={SS-MLP: A novel spectral-spatial MLP architecture for hyperspectral image classification},
author={Meng, Zhe and Zhao, Feng and Liang, Miaomiao},
journal={Remote Sensing},
volume={13},
number={20},
pages={4060},
year={2021},
publisher={MDPI}
}
- MLP-Mixer: An all-MLP Architecture for Vision https://arxiv.org/abs/2105.01601
- mlp-mixer-pytorch https://github.com/lucidrains/mlp-mixer-pytorch