A Fusion of Transfer Learning with Osprey Optimization Algorithm Based Student Engagement Detection for Improving Performance of Virtual Classroom Environments
This paper proposes the FTLSED-VCOOA framework, which integrates adaptive bilateral filtering, a fusion of SqueezeNet, Shallow CapsNets, and MobileNetV2 for feature extraction, a CNN-LSTM classifier, and the Osprey Optimization Algorithm for hyperparameter tuning to effectively detect student engagement and improve performance in virtual classroom environments.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Drowning in papers in your field?
Get daily digests of the most novel papers matching your research keywords — with technical summaries, in your language.