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Collaborative Learning Network for Change Detection and Semantic Segmentation of Remote Sensing Images

文献类型：期刊论文

作者Zhu, Jiahang1,2; Zhou, Yuan1,2; Xu, Nuo1,2; Huo, Chunlei1,2
刊名IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
出版日期2023
卷号20页码:5
关键词Change detection collaborative learning semantic segmentation
ISSN号1545-598X
DOI10.1109/LGRS.2023.3329058
通讯作者Huo, Chunlei(clhuo@nlpr.ia.ac.cn)
英文摘要Change detection of high-resolution remote sensing images is more attractive, since it can not only identify areas of changes but also identify types of changes. In this context, simultaneous change detection and semantic segmentation are natural and necessary. However, traditional methods put less emphasis on the cooperation of the above two tasks. In this letter, a novel method is proposed to realize the collaborative learning of change detection and semantic segmentation. By elaborately exploring the relevance and consistency between change detection and semantic segmentation, the proposed method synchronously enhanced feature separability of two tasks, and it outperformed a single change detection network or semantic segmentation network. Specifically, the proposed approach extracts multilevel bitemporal features by a backbone network, followed by two layer-by-layer decoders for learning change features and semantic features. On one hand, the interactive fusion module (IFM) fuses the changing features and semantic features together to increase the collaboration between the two tasks. On the other hand, the contrastive loss (CL) enhances the constraints between the two tasks. The advantages of the proposed method are demonstrated with respect to change region detection and change-type identification.
资助项目National Natural Science Foundation of China[62071466] ; Fund of National Key Laboratory of Science and Technology on Remote Sensing Information and Imagery Analysis, Beijing Research Institute of Uranium Geology[6142A010402] ; Guangxi Natural Science Foundation[2018GXNSFBA281086]
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001108986600004
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Natural Science Foundation of China ; Fund of National Key Laboratory of Science and Technology on Remote Sensing Information and Imagery Analysis, Beijing Research Institute of Uranium Geology ; Guangxi Natural Science Foundation
源URL[http://ir.ia.ac.cn/handle/173211/54871]  
专题自动化研究所_模式识别国家重点实验室_遥感图像处理团队
通讯作者Huo, Chunlei
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence e, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Zhu, Jiahang,Zhou, Yuan,Xu, Nuo,et al. Collaborative Learning Network for Change Detection and Semantic Segmentation of Remote Sensing Images[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2023,20:5.
APA Zhu, Jiahang,Zhou, Yuan,Xu, Nuo,&Huo, Chunlei.(2023).Collaborative Learning Network for Change Detection and Semantic Segmentation of Remote Sensing Images.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,20,5.
MLA Zhu, Jiahang,et al."Collaborative Learning Network for Change Detection and Semantic Segmentation of Remote Sensing Images".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 20(2023):5.

入库方式： OAI收割

来源：自动化研究所

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