A Review on Emotional Recognition System Based E-learning: Technology and Challenges
Brain; Deep learning; E-learning; Learning systems; Body activities; Electronic learning (e-learning); Emotional recognition; Learning management system; Multiple technology; State-of-the-art technology; Engineering education
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Institute of Electrical and Electronics Engineers Inc.
2023
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| _version_ | 1833351478808412160 |
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| author | Fadahl Alhaboobi Z.A. Singh Sidhu M. Hilaluddin T. |
| author2 | 57226695179 |
| author_facet | 57226695179 Fadahl Alhaboobi Z.A. Singh Sidhu M. Hilaluddin T. |
| author_sort | Fadahl Alhaboobi Z.A. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Brain; Deep learning; E-learning; Learning systems; Body activities; Electronic learning (e-learning); Emotional recognition; Learning management system; Multiple technology; State-of-the-art technology; Engineering education |
| format | Conference Paper |
| id | my.uniten.dspace-26102 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | my.uniten.dspace-261022023-05-29T17:06:50Z A Review on Emotional Recognition System Based E-learning: Technology and Challenges Fadahl Alhaboobi Z.A. Singh Sidhu M. Hilaluddin T. 57226695179 57226688688 57226685408 Brain; Deep learning; E-learning; Learning systems; Body activities; Electronic learning (e-learning); Emotional recognition; Learning management system; Multiple technology; State-of-the-art technology; Engineering education Multiple technologies have been incorporated with learning management systems (LMSs) in order to facilitate electronic learning (e-learning) experience. Emotional recognition system (ERS) is one of those technologies for providing tutors with learners' emotions related data such as anger, sadness, happiness etc. Additionally, emotions can be recognized using data alike facial, body activities and brain activate. This paper provides an overview of ERS structure referring to the existing state of the art technology. Results showed that great contribution was made in terms of ERS classification score enhancement by using deep learning-based conventional neural networks (CNN) such as AlexNet, GoogleNet, Inception V3, ResNet50 and SqueezeNet classifiers. � 2021 IEEE. Final 2023-05-29T09:06:49Z 2023-05-29T09:06:49Z 2021 Conference Paper 10.1109/ICOTEN52080.2021.9493551 2-s2.0-85112348439 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112348439&doi=10.1109%2fICOTEN52080.2021.9493551&partnerID=40&md5=c8606c18ec864ea2a0a1125f9813532e https://irepository.uniten.edu.my/handle/123456789/26102 9493551 Institute of Electrical and Electronics Engineers Inc. Scopus |
| spellingShingle | Fadahl Alhaboobi Z.A. Singh Sidhu M. Hilaluddin T. A Review on Emotional Recognition System Based E-learning: Technology and Challenges |
| title | A Review on Emotional Recognition System Based E-learning: Technology and Challenges |
| title_full | A Review on Emotional Recognition System Based E-learning: Technology and Challenges |
| title_fullStr | A Review on Emotional Recognition System Based E-learning: Technology and Challenges |
| title_full_unstemmed | A Review on Emotional Recognition System Based E-learning: Technology and Challenges |
| title_short | A Review on Emotional Recognition System Based E-learning: Technology and Challenges |
| title_sort | review on emotional recognition system based e-learning: technology and challenges |
| url_provider | http://dspace.uniten.edu.my/ |