{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T09:04:40Z","timestamp":1774083880193,"version":"3.50.1"},"reference-count":57,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,12,3]],"date-time":"2018-12-03T00:00:00Z","timestamp":1543795200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61701046,41674107,41874119,41574064"],"award-info":[{"award-number":["61701046,41674107,41874119,41574064"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Youth Fund of Yangtze University","award":["2016CQN10"],"award-info":[{"award-number":["2016CQN10"]}]},{"name":"Open Fund of Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University), Ministry of Education","award":["NO K2018-15"],"award-info":[{"award-number":["NO K2018-15"]}]},{"name":"the Undergraduate Training Programs for Innovation and Entrepreneurship of Yangtze University","award":["2017009"],"award-info":[{"award-number":["2017009"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In order to solve the problem of face recognition in complex environments being vulnerable to illumination change, object rotation, occlusion, and so on, which leads to the imprecision of target position, a face recognition algorithm with multi-feature fusion is proposed. This study presents a new robust face-matching method named SR-CNN, combining the rotation-invariant texture feature (RITF) vector, the scale-invariant feature transform (SIFT) vector, and the convolution neural network (CNN). Furthermore, a graphics processing unit (GPU) is used to parallelize the model for an optimal computational performance. The Labeled Faces in the Wild (LFW) database and self-collection face database were selected for experiments. It turns out that the true positive rate is improved by 10.97\u201313.24% and the acceleration ratio (the ratio between central processing unit (CPU) operation time and GPU time) is 5\u20136 times for the LFW face database. For the self-collection, the true positive rate increased by 12.65\u201315.31%, and the acceleration ratio improved by a factor of 6\u20137.<\/jats:p>","DOI":"10.3390\/s18124237","type":"journal-article","created":{"date-parts":[[2018,12,3]],"date-time":"2018-12-03T06:02:09Z","timestamp":1543816929000},"page":"4237","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Face Recognition Using the SR-CNN Model"],"prefix":"10.3390","volume":"18","author":[{"given":"Yu-Xin","family":"Yang","sequence":"first","affiliation":[{"name":"School of Computer Science, Yangtze University, Jingzhou 434023, China"},{"name":"National Demonstration Center for Experimental Electrical and Electronic Education, Yangtze University, Jingzhou 434023, China"}],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Chang","family":"Wen","sequence":"additional","affiliation":[{"name":"School of Computer Science, Yangtze University, Jingzhou 434023, China"}],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Kai","family":"Xie","sequence":"additional","affiliation":[{"name":"National Demonstration Center for Experimental Electrical and Electronic Education, Yangtze University, Jingzhou 434023, China"},{"name":"School of Electronic and Information, Yangtze University, Jingzhou 434023, China"}],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Fang-Qing","family":"Wen","sequence":"additional","affiliation":[{"name":"National Demonstration Center for Experimental Electrical and Electronic Education, Yangtze University, Jingzhou 434023, China"},{"name":"School of Electronic and Information, Yangtze University, Jingzhou 434023, China"}],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Guan-Qun","family":"Sheng","sequence":"additional","affiliation":[{"name":"National Demonstration Center for Experimental Electrical and Electronic Education, Yangtze University, Jingzhou 434023, China"},{"name":"School of Electronic and Information, Yangtze University, Jingzhou 434023, China"}],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Xin-Gong","family":"Tang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Exploration Technologies for Oil and Gas Resources, Yangtze University, Jingzhou 434023, China"}],"role":[{"role":"author","vocab":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.neucom.2015.02.093","article-title":"Face matching with an a-contrario false detection control","volume":"173","author":"Martino","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_2","first-page":"150","article-title":"Pose invariant face recognition: 3D model from single photo","volume":"89","author":"Alfalou","year":"2016","journal-title":"Opt. 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