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However, most of facial expression recognition methods have not obtained satisfactory results based on low\u2010level features. The existed methods used in facial expression recognition encountered the major issues of linear inseparability, large computational burden, and data redundancy. To obtain satisfactory results, we propose an innovative deep learning (DL) model using the kernel entropy component analysis network (KECANet) and directed acyclic graph support vector machine (DAGSVM). We use the KECANet in the feature extraction stage. In the stage of output, binary hashing and blockwise histograms are adopted. We sent the final output features to the DAGSVM classifier for expression recognition. We test the performance of our proposed method on three databases of CK+, JAFFE, and CMU Multi\u2010PIE. According to the experiment results, the proposed method can learn high\u2010level features and provide more recognition information in the stage of training, obtaining a higher recognition rate.<\/jats:p>","DOI":"10.1155\/2021\/6616158","type":"journal-article","created":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T18:38:54Z","timestamp":1609871934000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Facial Expression Recognition Using Kernel Entropy Component Analysis Network and DAGSVM"],"prefix":"10.1155","volume":"2021","author":[{"given":"Xiangmin","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2159-869X","authenticated-orcid":false,"given":"Li","family":"Ke","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Du","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinghui","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaodi","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,1,5]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11062-019-09775-y"},{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-018-6954-9"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/taffc.2016.2563432"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-017-1121-y"},{"key":"e_1_2_10_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00530-019-00628-6"},{"key":"e_1_2_10_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/tmm.2017.2713408"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/tsmc.2019.2897330"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-018-5909-5"},{"key":"e_1_2_10_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2017.2716952"},{"key":"e_1_2_10_10_2","doi-asserted-by":"publisher","DOI":"10.1108\/jices-07-2019-0072"},{"key":"e_1_2_10_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/34.598228"},{"key":"e_1_2_10_12_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13735-018-0153-3"},{"key":"e_1_2_10_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11663-018-1254-3"},{"key":"e_1_2_10_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2016.01.002"},{"key":"e_1_2_10_15_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-018-0556-3"},{"key":"e_1_2_10_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00371-019-01627-4"},{"key":"e_1_2_10_17_2","doi-asserted-by":"publisher","DOI":"10.1049\/el.2018.7871"},{"key":"e_1_2_10_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/taslp.2014.2339736"},{"key":"e_1_2_10_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2844093"},{"key":"e_1_2_10_20_2","doi-asserted-by":"publisher","DOI":"10.1002\/int.21948"},{"key":"e_1_2_10_21_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-016-9556-4"},{"key":"e_1_2_10_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.09.129"},{"key":"e_1_2_10_23_2","first-page":"205","article-title":"Image recognition method of multi-cluster kiwifruit in field based on convolutional neural networks","volume":"34","author":"Fu L.","year":"2018","journal-title":"Transactions of the Chinese Society of Agricultural Engineering"},{"key":"e_1_2_10_24_2","doi-asserted-by":"crossref","unstructured":"LiongV. 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