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By replacing conventional convolution modules with an RDCU, which adopts a deformable convolutional neural network within a residual network structure, the proposed method enhances the module\u2019s capacity to learn intricate details such as building shapes. Furthermore, AMSA is introduced into the skip connection function to enhance feature expression and positions through content\u2013position enhancement operations and content\u2013content enhancement operations. Moreover, AMSA integrates an additional fusion channel attention mechanism to aid in identifying cross-channel feature expression Intersection over Union (IoU) score differences. For the Massachusetts dataset, the proposed method achieves an Intersection over Union (IoU) score of 89.99%, PA (Pixel Accuracy) score of 93.62%, and Recall score of 89.22%. For the WHU Satellite dataset I, the proposed method achieves an IoU score of 86.47%, PA score of 92.45%, and Recall score of 91.62%, For the INRIA dataset, the proposed method achieves an IoU score of 80.47%, PA score of 90.15%, and Recall score of 85.42%.<\/jats:p>","DOI":"10.3390\/rs15205048","type":"journal-article","created":{"date-parts":[[2023,10,20]],"date-time":"2023-10-20T11:53:56Z","timestamp":1697802836000},"page":"5048","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Recurrent Residual Deformable Conv Unit and Multi-Head with Channel Self-Attention Based on U-Net for Building Extraction from Remote Sensing Images"],"prefix":"10.3390","volume":"15","author":[{"given":"Wenling","family":"Yu","sequence":"first","affiliation":[{"name":"School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China"},{"name":"Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2268-6176","authenticated-orcid":false,"given":"Bo","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China"},{"name":"Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China"},{"name":"Jiangxi Province Engineering Research Center of Surveying, Mapping and Geographic Information, Nanchang 330025, China"}]},{"given":"Hua","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China"},{"name":"Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China"},{"name":"Jiangxi Province Engineering Research Center of Surveying, Mapping and Geographic Information, Nanchang 330025, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7198-4735","authenticated-orcid":false,"given":"Guohua","family":"Gou","sequence":"additional","affiliation":[{"name":"State Key Laboratory Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430070, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"842","DOI":"10.1080\/01431161.2017.1392642","article-title":"Enhanced automatic detection of human settlements using Sentinel-1 interferometric coherence","volume":"39","author":"Corbane","year":"2018","journal-title":"Int. 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