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In these steps, the contribution is expressed by using strategic face points and interprets motions as action units extracted by the FACS system. The second contribution is at the level of the classification step, where two classifiers were used: Kohonen self-organizing maps (KSOM) and multilayer perceptron (MLP) in order to obtain the best results. The obtained results show that the recognition rate of basic emotions has improved, and the running time was minimized by reducing resource use.<\/jats:p>","DOI":"10.4018\/ijse.2019010102","type":"journal-article","created":{"date-parts":[[2019,9,20]],"date-time":"2019-09-20T14:15:22Z","timestamp":1568988922000},"page":"38-53","source":"Crossref","is-referenced-by-count":4,"title":["Emotion Recognition Approach Using Multilayer Perceptron Network and Motion Estimation"],"prefix":"10.4018","volume":"10","author":[{"given":"Mohamed","family":"Berkane","sequence":"first","affiliation":[{"name":"University of Oum el Bouaghi, Province of Oum El Bouaghi, Algeria"}]},{"given":"Kenza","family":"Belhouchette","sequence":"additional","affiliation":[{"name":"University of Oum el Bouaghi, Province of Oum El Bouaghi, Algeria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7313-5406","authenticated-orcid":true,"given":"Hacene","family":"Belhadef","sequence":"additional","affiliation":[{"name":"University of Constantine 2, Constantine, Algeria"}]}],"member":"2432","reference":[{"key":"IJSE.2019010102-0","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2005.12.021"},{"key":"IJSE.2019010102-1","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2004.05.009"},{"key":"IJSE.2019010102-2","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.98.2.224"},{"key":"IJSE.2019010102-3","unstructured":"Belhouchet, K., Berkane, M., & Belhadef, H. 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