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Then, the feature discrimination loss function is used to constrain the diversity of channel characteristics, so as to enhance the feature discrimination ability of local similar areas.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The experimental results show that the recognition accuracy of the proposed method for oral mucosal disease is the highest at 91.16%, and is about 6% ahead of other advanced methods. In addition, DSDF has recall of 90.87% and F1 of 90.60%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Convolutional neural networks can effectively capture the visual features of the oral mucosal disease lesions, and the distinguished visual features of different oral lesions can be extracted better using dynamic self\u2010attention and feature discrimination loss function, which is conducive to the auxiliary diagnosis of oral mucosal diseases.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/odi.14732","type":"journal-article","created":{"date-parts":[[2023,9,20]],"date-time":"2023-09-20T23:48:39Z","timestamp":1695253719000},"page":"3094-3107","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Oral mucosal disease recognition based on dynamic\n                    <scp>self\u2010attention<\/scp>\n                    and feature discriminant loss"],"prefix":"10.1111","volume":"30","author":[{"given":"Fei","family":"Xie","sequence":"first","affiliation":[{"name":"Xi'an Key Laboratory of Human\u2010Machine Integration and Control Technology for Intelligent Rehabilitation Xijing University  Xi'an China"},{"name":"School of AOAIR Xidian University  Xi'an China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8701-2669","authenticated-orcid":false,"given":"Pengfei","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology Northwest University  Xi'an China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyi","family":"Xi","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology Northwest University  Xi'an 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Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,9,20]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TLA.2016.7430097"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mlwa.2021.100036"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2019.11.042"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/int.22691"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/CANCERS13061291"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2973812"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2018.8363547"},{"key":"e_1_2_10_9_1","first-page":"1319","volume-title":"International conference on machine learning","author":"Goodfellow 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