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MSF-Net: A multiscale supervised fusion network for building change detection in high-resolution remote sensing images
2022
IEEE Access
Building change detection is a primary task in the application of remote sensing images, especially in city land resource management and urbanization process assesment. Due to the rich textural features of remote sensing images and the multiscale characteristics of buildings, it is still a huge challenge to effectively filter out irrelevant change information (e.g., roads) and fuse multiscale building features. To date, deep learning-based methods have demonstrated powerful capabilities in this
doi:10.1109/access.2022.3160163
fatcat:fmh7uts5svfyznu2h55uenve5y