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In this paper, we propose a facial expression recognition network based on wide attention (WA) and a multi-scale fusion (MF) mechanism (wide attention\u00a0and multi-scale fusion [WAMF]). WA by extracting the background information of facial expression images while focusing on texture information, thus achieving better feature extraction. The MF mechanism is added at the connection points of layers in ResNet, where features extracted from each upper layer are fused using different-sized convolutional kernels and input into the lower layer. Finally, a viewpoint-invariant Capsule Net is used as the classification network after receiving the feature maps. The proposed WAMF model was applied to two publicly available datasets, CK+ and Jaffe, achieving excellent recognition rates of 98.98% and 98.46%, respectively.<\/jats:p>","DOI":"10.1177\/18761364241296439","type":"journal-article","created":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T00:12:31Z","timestamp":1735776751000},"page":"286-301","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Research on facial expression recognition based on wide attention and multi-scale fusion mechanism"],"prefix":"10.1177","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-5459-0220","authenticated-orcid":false,"given":"Daipeng","family":"Guo","sequence":"first","affiliation":[{"name":"School of Mechatronic Engineering, Xi'an Technological University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Mu","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, Xi'an Technological University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, Xi'an Technological University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science, Xi'an Polytechnic University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,1]]},"reference":[{"key":"e_1_3_4_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-09806-5"},{"key":"e_1_3_4_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-021-00972-2"},{"key":"e_1_3_4_4_1","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.2000.3837"},{"key":"e_1_3_4_5_1","doi-asserted-by":"publisher","DOI":"10.1049\/iet-ipr.2020.0063"},{"key":"e_1_3_4_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-10271-3"},{"key":"e_1_3_4_7_1","first-page":"837","volume-title":"FERAtt: Facial expression recognition with attention net2019 IEEE\/CVF conference on computer vision and pattern recognition workshops (CVPRW)","author":"Fernandez PDM","year":"2019","unstructured":"Fernandez PDM, Pe\u00f1a FAG, Ren TI, et al. 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