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AuthorHussein, Ealaf S.
AuthorQidwai, Uvais
AuthorAl-Meer, Mohamed
Available date2024-05-07T05:39:57Z
Publication Date2020
Publication Name2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/ICIoT48696.2020.9089440
URIhttp://hdl.handle.net/10576/54671
AbstractEmotion recognition is the process of identifying human emotions. It is made possible by processing various modalities including facial expressions, speech signals, biometric signals, etc. Facial Emotion Recognition (FER) has been a growing field since the first works on FER by Ekman in 1970s where he adopted and improved the Facial Action Coding System (FACS). In human-computer interaction, FER is important for several applications in which the user's emotional state is required. The recent years witnessed hugbe advancements in artificial intelligence, specially neural networks; this paper uses convolutional neural network for FER to detect Emotional Stability. We achieve an accuracy of 81% on the classification of neutral, negative and positive emotions.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectCNNs
deep learning
Emotional Stability
Facial Emotion Recognition
Xception
TitleEmotional Stability Detection Using Convolutional Neural Networks
TypeConference Paper
Pagination136-140
dc.accessType Abstract Only


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