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Multiple auxiliary loss functions are used to constrain the network and reduce the noise in the deep features. In addition, an image enhancement method is also designed to solve the problem of insufficient annotated data. The experimental results show that the network can achieve 79.6% mIoU and 98.5% PA, which can meet the high standard requirements of magnetic tile manufacturing.<\/jats:p>","DOI":"10.3233\/jifs-232366","type":"journal-article","created":{"date-parts":[[2023,7,28]],"date-time":"2023-07-28T12:12:51Z","timestamp":1690546371000},"page":"9523-9532","source":"Crossref","is-referenced-by-count":1,"title":["Surface defect segmentation of magnetic tiles based on cross self-attention module"],"prefix":"10.1177","volume":"45","author":[{"given":"Hong","family":"Liu","sequence":"first","affiliation":[{"name":"School of Electrical and Elctronic Engineering, Hubei University of Technology, Hubei, China"}]},{"given":"Gaihua","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Tianjin University of Science & Technology, Tianjin, China"}]},{"given":"Qi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electrical and Elctronic Engineering, Hubei University of Technology, Hubei, China"}]},{"given":"Nengyuan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electrical and Elctronic Engineering, Hubei University of Technology, Hubei, China"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-232366_ref1","doi-asserted-by":"crossref","first-page":"3932","DOI":"10.1049\/iet-ipr.2020.0841","article-title":"Defect detection of printed circuit board based on lightweight deep convolution network","volume":"14","author":"Shen","year":"2020","journal-title":"IET Image Processing"},{"key":"10.3233\/JIFS-232366_ref2","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.optlaseng.2019.05.005","article-title":"A deep-learning-based approach for fast and robust steel surface defects classification","volume":"121","author":"Fu","year":"2019","journal-title":"Optics and Lasers in 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