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The substance of the research anticipates on the proposed modified GWO optimization which helps in maintaining the storage capacity with simple structures and provides high convergence. Enabling the optimization in the ensemble DCNN helps in tuning the internal parameters present in the classifier as well as helps in attaining best solution. The accomplishment of the proposed expression recognition model is evaluated utilizing the parameter metrics accuracy, precision, and recall that attained the values of 94.114%, 92.003%, and 95.734% which is more efficient.<\/jats:p>","DOI":"10.1142\/s0219467823500456","type":"journal-article","created":{"date-parts":[[2022,7,31]],"date-time":"2022-07-31T04:38:15Z","timestamp":1659242295000},"source":"Crossref","is-referenced-by-count":1,"title":["Hybrid Features and Deep Learning Model for Facial Expression Recognition From Videos"],"prefix":"10.1142","volume":"23","author":[{"given":"Priyanka A.","family":"Gavade","sequence":"first","affiliation":[{"name":"Department of Information Science and Engineering, SDM College of Engineering and Technology, Dhavalagiri, Dharwad 580002, Karnataka, India"}]},{"given":"Vandana S.","family":"Bhat","sequence":"additional","affiliation":[{"name":"Department of Information Science and Engineering, SDM College of Engineering and Technology, Dhavalagiri, Dharwad 580002, Karnataka, India"}]},{"given":"Jagadeesh","family":"Pujari","sequence":"additional","affiliation":[{"name":"Department of Information Science and Engineering, SDM College of Engineering and Technology, Dhavalagiri, Dharwad 580002, Karnataka, India"}]}],"member":"219","published-online":{"date-parts":[[2022,7,30]]},"reference":[{"key":"S0219467823500456BIB001","doi-asserted-by":"crossref","first-page":"14797","DOI":"10.1109\/ACCESS.2017.2724555","volume":"5","author":"Mehmood R. 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