The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Facial emotion recognition using deep learning: review and insights
Open accessAbstract
Automatic emotion recognition based on facial expression is an interesting research field, which has presented and applied in several areas such as safety, health and in human machine interfaces. Researchers in this field are interested in developing techniques to interpret, code facial expressions and extract these features in order to have a better prediction by computer. With the remarkable success of deep learning, the different types of architectures of this technique are exploited to achieve a better performance. The purpose of this paper is to make a study on recent works on automatic facial emotion recognition FER via deep learning. We underline on these contributions treated, the architecture and the databases used and we present the progress made by comparing the proposed methods and the results obtained. The interest of this paper is to serve and guide researchers by review recent works and providing insights to make improvements to this field.
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Cites
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Presentation and validation of the Radboud Faces Database
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AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild
Mollahosseini, A., Hasani, B., & Mahoor, M. H. (2019) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2017.2740923 · Cited by 2,338
Facial expression recognition based on Local Binary Patterns: A comprehensive study
Shan, C., Gong, S., & McOwan, P. W. (2009) · Image and Vision Computing · doi:10.1016/j.imavis.2008.08.005 · Cited by 2,300
Challenges in Representation Learning: A Report on Three Machine Learning Contests
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Reliable Crowdsourcing and Deep Locality-Preserving Learning for Expression Recognition in the Wild
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A 3D Facial Expression Database For Facial Behavior Research
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Going deeper in facial expression recognition using deep neural networks
Mollahosseini, A., Chan, D., & Mahoor, M. H. (2016) · 2016 IEEE Winter Conference on Applications of Computer Vision (WACV) · doi:10.1109/wacv.2016.7477450 · Cited by 1,086
Web-Based Database for Facial Expression Analysis
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Cited by
Multimodal Emotion Recognition using Deep Learning
Abdullah, S. M. S. A., Ameen, S. Y. A., M. Sadeeq, M. A., & Zeebaree, S. (2021) · Journal of Applied Science and Technology Trends · doi:10.38094/jastt20291 · Cited by 347
Emotion recognition in EEG signals using deep learning methods: A review
Jafari, M., Shoeibi, A., Khodatars, M., Bagherzadeh, S., Shalbaf, A., García, D. L., Gorriz, J. M., & Acharya, U. R. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107450 · Cited by 240
Metadata
- Authors
- Mellouk, W., & Handouzi, W.
- Venue
- Procedia Computer Science
- Publisher
- Elsevier BV
- Published
- 2020
- Volume
- 175
- Pages
- 689-694
- ISSN
- 1877-0509 (ISSN-L)
- OpenAlex
- W3048297990
- Cited by
- 339
- References
- 38
- FWCI
- 40.43
- Type
- conference paper
- Language
- en
- Open access
- diamond
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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