PyTorch implementation of deep residual involution network for hyperspectral image classification.
import torch
from DRIN import DRIN
model = DRIN(num_classes=16, channels=200)
model.eval()
print(model)
input = torch.randn(100, 200, 11, 11)
y = model(input)
print(y.size())
Deep residual involution network for hyperspectral image classification
Please cite our paper if you find it useful for your research.
@article{meng2021deep,
title={Deep residual involution network for hyperspectral image classification},
author={Meng, Zhe and Zhao, Feng and Liang, Miaomiao and Xie, Wen},
journal={Remote Sensing},
volume={13},
number={16},
pages={3055},
year={2021},
publisher={MDPI}
}
- Involution: Inverting the Inherence of Convolution for Visual Recognition https://arxiv.org/abs/2103.06255
- involution https://github.com/d-li14/involution