Communication publiée dans un périodique (Colloques, congrès, conférences scientifiques et actes) Emotion Recognition Based on Facial Expressions Using Convolutional Neural Network (CNN)
Begaj, S. ; TOPAL, Ali Osman ; ALI, Muhammad et al.
2020 • In Proceedings - 2020 International Conference on Computing, Networking, Telecommunications and Engineering Sciences Applications, CoNTESA 2020 , p. 58-63
Peer reviewed
Mots-clés :
CNN; Convolutional Neural Network; Data Preprocessing; Deep Learning; Facial Emotion Recognition; Facial Expression Recognition; FER; Image Recognition; Face recognition; Speech recognition; Emotion recognition; Facial emotions; Facial Expressions; Human faces; Learning techniques; Convolutional neural networks
Résumé :
[en] Over the last few years, there has been an increasing number of studies about facial emotion recognition because of the importance and the impact that it has in the interaction of humans with computers. With the growing number of challenging datasets, the application of deep learning techniques have all become necessary. In this paper, we study the challenges of Emotion Recognition Datasets and we also try different parameters and architectures of the Conventional Neural Networks (CNNs) in order to detect the seven emotions in human faces, such as: anger, fear, disgust, contempt, happiness, sadness and surprise. We have chosen iCV MEFED (Multi-Emotion Facial Expression Dataset) as the main dataset for our study, which is relatively new, interesting and very challenging. © 2020 IEEE.
Nom de la manifestation :
1st International Conference on Computing, Networking, Telecommunications and Engineering Sciences Applications, CoNTESA 2020
Titre du périodique :
Proceedings - 2020 International Conference on Computing, Networking, Telecommunications and Engineering Sciences Applications, CoNTESA 2020
Nombre de vues
171 (dont 11 Unilu)
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0 (dont 0 Unilu)
citations Scopus® sans auto-citations
33