Reference : Emotion Recognition Based on Facial Expressions Using Convolutional Neural Network (CNN)

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a journal
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/52193

Title :	Emotion Recognition Based on Facial Expressions Using Convolutional Neural Network (CNN)
Language :	English
Author, co-author :	Begaj, S. [Epoka University, Department of Computer Engineering, Tirana, Albania]
	Topal, Ali Osman [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)]
	Ali, Muhammad [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
	Ali, Muhammad [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
	Miraz, M. H. [> >]
	Ware, A. [> >]
	Soomro, S. [> >]
Publication date :	2020
Journal title :	Proceedings - 2020 International Conference on Computing, Networking, Telecommunications and Engineering Sciences Applications, CoNTESA 2020
Publisher :	Institute of Electrical and Electronics Engineers Inc.
Pages :	58-63
Peer reviewed :	Yes
Audience :	International
Event name :	1st International Conference on Computing, Networking, Telecommunications and Engineering Sciences Applications, CoNTESA 2020
Event date :	9 December 2020 through 10 December 2020
Keywords :	[en] CNN ; Convolutional Neural Network ; Data Preprocessing ; Deep Learning ; Facial Emotion Recognition ; Facial Expression Recognition ; FER ; Image Recognition ; Deep learning ; Face recognition ; Speech recognition ; Emotion recognition ; Facial emotions ; Facial Expressions ; Human faces ; Learning techniques ; Convolutional neural networks
Abstract :	[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.
Permalink :	http://hdl.handle.net/10993/52193
DOI :	10.1109/CoNTESA50436.2020.9302866
Commentary :	166254 9781728184883

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