Multi-Scale Feature Interaction Network for Remote Sensing Change Detection by Chong Zhang, Yonghong Zhang, Haifeng Lin

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MFINet: Multi-Scale Feature Interaction Network for Change Detection of High-Resolution Remote Sensing Images by Wuxu Ren, Zhongchen Wang, Min Xia, Haifeng Lin

“…Therefore, this paper proposes a multi-scale feature interaction network (MFINet). The network realizes the information interaction of multi-temporal images by inserting a bi-temporal feature interaction layer (BFIL) between backbone networks at the same level, guides the attention to focus on the difference region, and suppresses the interference. …”
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Multi-Level Attention Interactive Network for Cloud and Snow Detection Segmentation by Li Ding, Min Xia, Haifeng Lin, Kai Hu

“…In the last down-sampling, the Deep Multi-head Information Enhancement module combines a CNN and a Transformer structure to make deep semantic features more distinct and reduce redundant information. Then, the Feature Interactive and Fusion Up-sampling module enhances the information extraction of deep and shallow information and, then, guides and aggregates each to make the learned semantic features more comprehensive, which can better recover remote sensing images and increase the prediction accuracy. …”
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