{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T00:40:16Z","timestamp":1768264816131,"version":"3.49.0"},"reference-count":53,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T00:00:00Z","timestamp":1731974400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Postdoctoral Fellowship Program CPSF","award":["GZB20240849"],"award-info":[{"award-number":["GZB20240849"]}]},{"name":"Postdoctoral Fellowship Program CPSF","award":["ZR2024QD133"],"award-info":[{"award-number":["ZR2024QD133"]}]},{"name":"Postdoctoral Fellowship Program CPSF","award":["24CX06022A"],"award-info":[{"award-number":["24CX06022A"]}]},{"name":"Postdoctoral Fellowship Program CPSF","award":["41776182"],"award-info":[{"award-number":["41776182"]}]},{"name":"Natural Science Foundation of Shandong Provincial","award":["GZB20240849"],"award-info":[{"award-number":["GZB20240849"]}]},{"name":"Natural Science Foundation of Shandong Provincial","award":["ZR2024QD133"],"award-info":[{"award-number":["ZR2024QD133"]}]},{"name":"Natural Science Foundation of Shandong Provincial","award":["24CX06022A"],"award-info":[{"award-number":["24CX06022A"]}]},{"name":"Natural Science Foundation of Shandong Provincial","award":["41776182"],"award-info":[{"award-number":["41776182"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["GZB20240849"],"award-info":[{"award-number":["GZB20240849"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["ZR2024QD133"],"award-info":[{"award-number":["ZR2024QD133"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["24CX06022A"],"award-info":[{"award-number":["24CX06022A"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["41776182"],"award-info":[{"award-number":["41776182"]}]},{"name":"National Natural Science Foundation of China","award":["GZB20240849"],"award-info":[{"award-number":["GZB20240849"]}]},{"name":"National Natural Science Foundation of China","award":["ZR2024QD133"],"award-info":[{"award-number":["ZR2024QD133"]}]},{"name":"National Natural Science Foundation of China","award":["24CX06022A"],"award-info":[{"award-number":["24CX06022A"]}]},{"name":"National Natural Science Foundation of China","award":["41776182"],"award-info":[{"award-number":["41776182"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The precise extraction of building footprints using remote sensing technology is increasingly critical for urban planning and development amid growing urbanization. However, considering the complexity of building backgrounds, diverse scales, and varied appearances, accurately and efficiently extracting building footprints from various remote sensing images remains a significant challenge. In this paper, we propose a novel network architecture called ME-FCN, specifically designed to perceive and optimize multi-scale features to effectively address the challenge of extracting building footprints from complex remote sensing images. We introduce a Squeeze-and-Excitation U-Block (SEUB), which cascades multi-scale semantic information exploration in shallow feature maps and incorporates channel attention to optimize features. In the network\u2019s deeper layers, we implement an Adaptive Multi-scale feature Enhancement Block (AMEB), which captures large receptive field information through concatenated atrous convolutions. Additionally, we develop a novel Dual Multi-scale Attention (DMSA) mechanism to further enhance the accuracy of cascaded features. DMSA captures multi-scale semantic features across both channel and spatial dimensions, suppresses redundant information, and realizes multi-scale feature interaction and fusion, thereby improving the overall accuracy and efficiency. Comprehensive experiments on three datasets demonstrate that ME-FCN outperforms mainstream segmentation methods.<\/jats:p>","DOI":"10.3390\/rs16224305","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T06:06:54Z","timestamp":1731996414000},"page":"4305","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["ME-FCN: A Multi-Scale Feature-Enhanced Fully Convolutional Network for Building Footprint Extraction"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9933-1955","authenticated-orcid":false,"given":"Hui","family":"Sheng","sequence":"first","affiliation":[{"name":"College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao 266404, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaoteng","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao 266404, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao 266404, China"},{"name":"Land Surveying and Mapping Institute of Shandong Province, Jinan 250102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9130-4584","authenticated-orcid":false,"given":"Shiqing","family":"Wei","sequence":"additional","affiliation":[{"name":"College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao 266404, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6758-9863","authenticated-orcid":false,"given":"Mingming","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao 266404, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yasir","family":"Muhammad","sequence":"additional","affiliation":[{"name":"College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao 266404, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/MGRS.2017.2762307","article-title":"Deep learning in remote sensing: A comprehensive review and list of resources","volume":"5","author":"Zhu","year":"2017","journal-title":"IEEE Geosci. 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