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DDECNet: Dual-Branch Difference Enhanced Network with Novel Efficient Cross-Attention for Remote Sensing Change Detection

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成果类型:
会议论文
作者:
Wei Wang;Qing Su;Xin Wang
作者机构:
[Qing Su] School of Computer Science and Technology, Changsha University of Science and Technology, 410114, Changsha, China
[Xin Wang] School of Physics and Electronic Science, Changsha University of Science and Technology, 410114, Changsha, China
[Wei Wang] School of Computer Science and Technology, Changsha University of Science and Technology, 410114, Changsha, China<&wdkj&>School of Physics and Electronic Science, Changsha University of Science and Technology, 410114, Changsha, China
语种:
英文
年:
2025
页码:
125-136
会议名称:
Advanced Intelligent Computing Technology and Applications: 21st International Conference, ICIC 2025, Ningbo, China, July 26–29, 2025, Proceedings, Part I
出版地:
Berlin, Heidelberg
出版者:
Springer-Verlag
ISBN:
978-981-96-9862-2
机构署名:
本校为第一机构
院系归属:
物理与电子科学学院
摘要:
To address pseudo-changes caused by background variations in remote sensing change detection, a dual-branch difference-enhanced network (DDECNet) with an efficient cross-attention mechanism is proposed. The Dual-Temporal Interaction Augmentation Module (DTIAM) enhances semantic consistency during bi-temporal feature interaction through temporal state alignment. The Difference Feature Enhancement and Supplementary Module (DFESM) reduces information loss in differential feature extraction using dual-branch feedback mechanisms for bidirectional temporal state correction. Differential features and...

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