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YOLOv5 Based Student Engagement and Emotional States Detection in E-Classes

The rapid expansion of E-learning environments has highlighted the critical issue of cyberbullying within digital classrooms. This study introduces a novel approach for early detection of cyberbullying by analyzing student engagement and emotional states in real time. Our SER-YOLO model fuses an adv...

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Main Authors: Wang S., Shibghatullah A.S., Keoy K.H., Iqbal J.
Other Authors: 58984450100
Format: Article
Published: ALife Robotics Corporation Ltd 2025
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spelling my.uniten.dspace-369782025-03-03T15:46:17Z YOLOv5 Based Student Engagement and Emotional States Detection in E-Classes Wang S. Shibghatullah A.S. Keoy K.H. Iqbal J. 58984450100 24067964300 14054280900 58563731500 The rapid expansion of E-learning environments has highlighted the critical issue of cyberbullying within digital classrooms. This study introduces a novel approach for early detection of cyberbullying by analyzing student engagement and emotional states in real time. Our SER-YOLO model fuses an advanced You Only Look Once version 5 (YOLOv5) with a Student Emotion Recognition system, enriched by sophisticated methodological improvements. It features Soft NMS to refine the Non-Maximum Suppression (NMS) process, embeds the Channel Attention (CA) module to augment the network's backbone, and employs Enhanced Intersection over Union (EIOU) for bounding box regression. This method proactively detects changes in student engagement and emotional states, providing an effective mechanism for the early detection and management of cyberbullying in E-learning environments. ? 2022 The Author. Final 2025-03-03T07:46:17Z 2025-03-03T07:46:17Z 2024 Article 10.57417/jrnal.10.4_357 2-s2.0-85204723100 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204723100&doi=10.57417%2fjrnal.10.4_357&partnerID=40&md5=6cf1c2464ba3c661b3d7520fc710405b https://irepository.uniten.edu.my/handle/123456789/36978 10 4 357 361 ALife Robotics Corporation Ltd Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description The rapid expansion of E-learning environments has highlighted the critical issue of cyberbullying within digital classrooms. This study introduces a novel approach for early detection of cyberbullying by analyzing student engagement and emotional states in real time. Our SER-YOLO model fuses an advanced You Only Look Once version 5 (YOLOv5) with a Student Emotion Recognition system, enriched by sophisticated methodological improvements. It features Soft NMS to refine the Non-Maximum Suppression (NMS) process, embeds the Channel Attention (CA) module to augment the network's backbone, and employs Enhanced Intersection over Union (EIOU) for bounding box regression. This method proactively detects changes in student engagement and emotional states, providing an effective mechanism for the early detection and management of cyberbullying in E-learning environments. ? 2022 The Author.
author2 58984450100
author_facet 58984450100
Wang S.
Shibghatullah A.S.
Keoy K.H.
Iqbal J.
format Article
author Wang S.
Shibghatullah A.S.
Keoy K.H.
Iqbal J.
spellingShingle Wang S.
Shibghatullah A.S.
Keoy K.H.
Iqbal J.
YOLOv5 Based Student Engagement and Emotional States Detection in E-Classes
author_sort Wang S.
title YOLOv5 Based Student Engagement and Emotional States Detection in E-Classes
title_short YOLOv5 Based Student Engagement and Emotional States Detection in E-Classes
title_full YOLOv5 Based Student Engagement and Emotional States Detection in E-Classes
title_fullStr YOLOv5 Based Student Engagement and Emotional States Detection in E-Classes
title_full_unstemmed YOLOv5 Based Student Engagement and Emotional States Detection in E-Classes
title_sort yolov5 based student engagement and emotional states detection in e-classes
publisher ALife Robotics Corporation Ltd
publishDate 2025
_version_ 1825816290964537344
score 13.244413

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