{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T21:55:32Z","timestamp":1778709332879,"version":"3.51.4"},"reference-count":40,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T00:00:00Z","timestamp":1714608000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Basic Research Project of Liaoning Provincial Department of Education \u201cTraining and Application of Multimodal Deep Neural Network Models for Vertical Fields\u201d","award":["JYTMS20231160"],"award-info":[{"award-number":["JYTMS20231160"]}]},{"name":"Basic Research Project of Liaoning Provincial Department of Education \u201cTraining and Application of Multimodal Deep Neural Network Models for Vertical Fields\u201d","award":["JG22DB488"],"award-info":[{"award-number":["JG22DB488"]}]},{"name":"Research on the Construction of a New Artificial Intelligence Technology and High Quality Education Service Supply System in the 14th Five Year Plan for Education Science in Liaoning Province, 2023\u20132025","award":["JYTMS20231160"],"award-info":[{"award-number":["JYTMS20231160"]}]},{"name":"Research on the Construction of a New Artificial Intelligence Technology and High Quality Education Service Supply System in the 14th Five Year Plan for Education Science in Liaoning Province, 2023\u20132025","award":["JG22DB488"],"award-info":[{"award-number":["JG22DB488"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>To address the various challenges in aluminum surface defect detection, such as multiscale intricacies, sensitivity to lighting variations, occlusion, and noise, this study proposes the AluDef-ClassNet model. Firstly, a Gaussian difference pyramid is utilized to capture multiscale image features. Secondly, a self-attention mechanism is introduced to enhance feature representation. Additionally, an improved residual network structure incorporating dilated convolutions is adopted to increase the receptive field, thereby enhancing the network\u2019s ability to learn from extensive information. A small-scale dataset of high-quality aluminum surface defect images is acquired using a CCD camera. To better tackle the challenges in surface defect detection, advanced deep learning techniques and data augmentation strategies are employed. To address the difficulty of data labeling, a transfer learning approach based on fine-tuning is utilized, leveraging prior knowledge to enhance the efficiency and accuracy of model training. In dataset testing, our model achieved a classification accuracy of 97.6%, demonstrating significant advantages over other classification models.<\/jats:p>","DOI":"10.3390\/s24092914","type":"journal-article","created":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T07:04:14Z","timestamp":1714633454000},"page":"2914","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Surface Defect Detection of Aluminum Profiles Based on Multiscale and Self-Attention Mechanisms"],"prefix":"10.3390","volume":"24","author":[{"given":"Yichuan","family":"Shao","sequence":"first","affiliation":[{"name":"School of Intelligent Science and Engineering, Shenyang University, Shenyang 110044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuo","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Shenyang University, Shenyang 110044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Science, Shenyang University of Technology, Shenyang 110044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5533-7645","authenticated-orcid":false,"given":"Le","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Intelligent Science and Engineering, Shenyang University, Shenyang 110044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haijing","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Intelligent Science and Engineering, Shenyang University, Shenyang 110044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"172152","DOI":"10.1109\/ACCESS.2020.3025165","article-title":"Two-Stream Convolutional Neural Network Based on Gradient Image for Aluminum Profile Surface Defects Classification and Recognition","volume":"8","author":"Duan","year":"2020","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1493","DOI":"10.1109\/TIM.2019.2915404","article-title":"An End-to-End Steel Surface Defect Detection Approach via Fusing Multiple Hierarchical Features","volume":"69","author":"He","year":"2020","journal-title":"IEEE Trans. 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