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The algorithm incorporates a fast lightweight feature extraction structure, the number of parameters and computation of the model are reduced while preserving the spatial information, thus improving the target detection performance. A multi\u2010scale feature fusion module is introduced, enabling the extraction of more comprehensive and richer features compared to traditional single\u2010scale methods, to better support defect detection tasks. Additionally, a receptive field attention structure, Receptive Field Attention Neck, is designed in the Neck part to expand the model's receptive field and reduce computational complexity, significantly improving detection accuracy for small defects. This allows the model to effectively capture both global and local features in complex industrial scenarios. The effectiveness of the improved FMR\u2010YOLO algorithm is validated on two industrial surface defect datasets: GC10\u2010DET and NEU\u2010DET. Experimental results show that the mAP@0.5 detection accuracy has increased by 4.5% and 5.1% on the GC10\u2010DET and NEU\u2010DET datasets, respectively, with a parameter size of merely 2.7\u00a0M.<\/jats:p>","DOI":"10.1049\/ipr2.70009","type":"journal-article","created":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T21:54:36Z","timestamp":1741730076000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["FMR\u2010YOLO: An improved YOLOv8 algorithm for steel surface defect detection"],"prefix":"10.1049","volume":"19","author":[{"given":"Yongjing","family":"Ni","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering Hebei University of Science and Technology  Shijiazhuang China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1134-3071","authenticated-orcid":false,"given":"Qi","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering Hebei University of Science and Technology  Shijiazhuang China"}]},{"given":"Xiuqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering Hebei University of Science and Technology  Shijiazhuang China"}]}],"member":"265","published-online":{"date-parts":[[2025,2,26]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.3390\/s20061562"},{"key":"e_1_2_10_3_1","doi-asserted-by":"crossref","unstructured":"Li Z. 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