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A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images

深度监督影像融合网络DSIFN用于高分辨率双时相遥感影像变化检测

Official implement of the Paper：A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images. If you find this work helps in your research, please consider citing:

论文《A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sening images》的官方模型代码。如果该代码对你的研究有所帮助，烦请引用：

Zhang, C., Yue, P., Tapete, D., Jiang, L., Shangguan, B., Huang, L., & Liu, G. (2020). A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images. ISPRS Journal of Photogrammetry and Remote Sensing, 166, 183-200.

Introduction

This repository includes DSIFN implementations in PyTorch and Keras version and datasets in the paper

该库包含了DSIFN网络的pytorch和keras版本的代码实现以及论文中使用的数据

Model Structure

The overview of Deeply supervised image fusion network (DSIFN). The network has two sub-networks: DFEN with pre-trained VGG16 as the backbone for deep feature extraction and DDN with deep feature fusion modules and deep supervision branches for change map reconstruction.

深度监督影像融合网络框架。该网络包含两个子网络：DFEN（深度特征提取网络）以VGG16为网络基底实现深度特征提取；DDN（差异判别网络）由深度特征融合模块和深度监督分支搭建实现影像变化图重建。

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Pytorch version requirements

Keras version requirements

Reference

Zhang, C., Yue, P., Tapete, D., Jiang, L., Shangguan, B., Huang, L., & Liu, G. (2020). A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images. ISPRS Journal of Photogrammetry and Remote Sensing, 166, 183-200.

License

Code and datasets are released for non-commercial and research purposes only. For commercial purposes, please contact the authors.