{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,1,13]],"date-time":"2024-01-13T00:39:27Z","timestamp":1705106367294},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684802","type":"print"},{"value":"9781643684819","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T00:00:00Z","timestamp":1705017600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,12]]},"abstract":"<jats:p>Human emotions identification has many applications, including human-computer interaction, illogical analysis, medical diagnosis, data-driven animation, and human-robot interaction. This paper presents a classification model, ConvNet that extracts features from facial images using techniques such as local binary patterns (LBP), convolutional neural networks (CNN), and region-based oriented FAST and rotational BRIEF (ORB). This model converges quickly. Experiment show that ConvNet outperforms existing methods with a precision of 98.13% on the CK+ dataset and 92.05 % on the JAFFE dataset.<\/jats:p>","DOI":"10.3233\/faia231252","type":"book-chapter","created":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T12:57:03Z","timestamp":1705064223000},"source":"Crossref","is-referenced-by-count":0,"title":["Improving Facial Emotional Recognition Using Convolution Neural Network with Minimal Layer"],"prefix":"10.3233","author":[{"given":"Rogerant","family":"Tshibangu","sequence":"first","affiliation":[{"name":"Electrical Engineering Department, Mangosuthu University of Technology, Durban, South Africa, 4031"}]},{"given":"Jules R.","family":"Tapamo","sequence":"additional","affiliation":[{"name":"Discipline of Electrical, Electronic and Computer Engineering, University of Kwazulu-Natal, Durban, South Africa, 4041"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Electronics, Communications and Networks"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA231252","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T12:57:04Z","timestamp":1705064224000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA231252"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,12]]},"ISBN":["9781643684802","9781643684819"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia231252","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,12]]}}}