https://github.com/Bobholamovic/ESCNet

ESCNet: An End-to-End Superpixel-Enhanced Change Detection Network for Very High Resolution Remote Sensing Images
https://github.com/Bobholamovic/ESCNet

change-detection convolutional-neural-networks deep-learning pytorch remote-sensing

Last synced: 3 months ago
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ESCNet: An End-to-End Superpixel-Enhanced Change Detection Network for Very High Resolution Remote Sensing Images

• Host: GitHub
• URL: https://github.com/Bobholamovic/ESCNet
• Owner: Bobholamovic
• License: mit
• Created: 2021-01-15T12:10:53.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2021-07-07T08:07:31.000Z (over 3 years ago)
• Last Synced: 2024-07-23T03:40:34.645Z (4 months ago)
• Topics: change-detection, convolutional-neural-networks, deep-learning, pytorch, remote-sensing
• Language: C++
• Homepage:
• Size: 18 MB
• Stars: 45
• Watchers: 2
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-remote-sensing-change-detection - Zhang H, Lin M, Yang G, et al. ESCNet: An End-to-End Superpixel-Enhanced Change Detection Network for Very-High-Resolution Remote Sensing Images

README

        
# ESCNet

This repo is an official implementation of ["ESCNet: An End-to-End Superpixel-Enhanced Change Detection Network for Very High Resolution Remote Sensing Images."](https://ieeexplore.ieee.org/document/9474911)

## Dependencies

> pytorch==1.3.1  

  scipy==1.3.1  

  scikit-image==0.15.0  

Tested using Python 3.7.4 on Ubuntu 16.04. nvcc version was 9.2.148.

## How-To

```bash

cd lib

. install.sh

cd ..

python demo.py

```

## Citation

If you find this work interesting in your research, please cite:

```

@ARTICLE{9474911,  

  author={Zhang, Hongyan and Lin, Manhui and Yang, Guangyi and Zhang, Liangpei},  

  journal={IEEE Transactions on Neural Networks and Learning Systems},  

  title={ESCNet: An End-to-End Superpixel-Enhanced Change Detection Network for Very-High-Resolution Remote Sensing Images},  

  year={2021},  

  volume={},  

  number={},  

  pages={1-15},  

  doi={10.1109/TNNLS.2021.3089332}

} 

```