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Feature Decomposition-Optimization-Reorganization Network for Building Change Detection in Remote Sensing Images
Building change detection plays an imperative role in urban construction and development. Although the deep neural network has achieved tremendous success in remote sensing image building change detection, it is still fraught with the problem of generating broken detection boundaries and separation of dense buildings, which tends to produce saw-tooth boundaries. In this work, we propose a feature decomposition-optimization-reorganization network for building change detection. The maindoi:10.3390/rs14030722 fatcat:2e3n76zcgvbcpiasjzkjsrqjeq