What question did this study set out to answer?

To investigate the use of deep learning algorithms for detecting student engagement in educational settings.

April 1, 2026Open Access

Deep Learning-based Student Engagement Detection using Yolo Classification for Intelligent Classroom Monitoring

Puntos clave

To investigate the use of deep learning algorithms for detecting student engagement in educational settings.
Utilized Yolo classification framework for real-time monitoring.
Analyzed classroom video feeds to assess engagement levels.
Compared performance metrics against traditional methods.
Achieved high accuracy in detecting varying levels of student engagement.
Demonstrated improved monitoring efficiency in classroom settings.

Resumen

UGC-CARE list, New UGC-CARE Reference List, UGC CARE Journals, ugc care list of journal, ugc care list, UGC Approved list, list of ugc approved journal, ugc approved journal,IJRAR - international Research Journal,IJRAR.ORG,Ijrar.org, International Journal of Research and Analytical Reviews (IJRAR) , UGC Approved journal, ugc approved,ugc, ugc certify, publish free of cost, free publication, UGC and ISSN Approved , International Peer Reviewed, Open Access Journal , e ISSN 2348 –1269, Print ISSN 2349-5138, ISSN: 2348 –1269, Impact Factor : 5.75 , E- journal, Low Cost INR 500, Free Publication

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Cite This Study

Dalan et al. (Thu,) studied this question.

synapsesocial.com/papers/69ccb6e416edfba7beb889a3 https://doi.org/https://doi.org/10.56975/ijrar.v13i1.330096

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