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.

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

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。

• Python3.7
• PyTorch 1.6.0
• torchversion 0.7.0

• Python 3.6
• Tensorflow-gpu 1.13.1
• Keras 2.2.4

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.

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