Diverse distant-students deep emotion recognition and visualization

dc.contributor.authorHarb, Ala'a
dc.contributor.authorGad, Abdalla
dc.contributor.authorYaghi, Maha
dc.contributor.authorETAL..
dc.date.accessioned2024-02-26T07:02:33Z
dc.date.available2024-02-26T07:02:33Z
dc.date.issued2023-11
dc.descriptionRecently, the Arab region had to move to online education delivery to offer students the flexibility to pursue their education anywhere.
dc.description.abstractDistance learning through online platforms has recently emerged as a significant addition to the educational system, providing support and enhancing traditional delivery modes in schools. Instructors need visual feedback to monitor students’ engagement. This research aims to investigate the emotional state of culturally diverse students in the country throughout the lecture and provide teachers with an interactive dashboard to monitor students’ emotional states during a particular lecture. We collected a specialized dataset that includes Arab students posing for various emotions specifically related to lecture scenarios. Face detection and alignment algorithm is then applied. Finally, we utilize Neural Architecture Search (NAS) to optimize emotion classification architecture. The overall accuracy of the model is 86.29% on our collected dataset and 98.84% on the CK+ dataset. The live testing of the system shows the emotions clearly with real-time feedback. The AI-powered dashboard gives instructors insights into student engagement during distance learning, which induces data-driven decisions to optimize teaching. Keywords: Neural Architecture Search (NAS), Deep learning, Facial emotion recognition, Face alignment, Computer vision, Data augmentation
dc.identifier.citationHarb, A. A., Gad, A., Yaghi, M., Alhalabi, M., Zia, H., Yousaf, J., ... & Ghazal, M. (2023). Diverse distant-students deep emotion recognition and visualization. Computers and Electrical Engineering, 111, 108963.
dc.identifier.doihttps://doi.org/10.1016/j.compeleceng.2023.108963
dc.identifier.urihttps://dspace.adu.ac.ae/handle/1/1290
dc.language.isoen
dc.publisherElsevier
dc.titleDiverse distant-students deep emotion recognition and visualization
dc.typeArticle

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