Engagement Detection with Multi-Task Training in E-Learning Environments. (arXiv:2204.04020v1 [cs.CV])

Recognition of user interaction, in particular engagement detection, became
highly crucial for online working and learning environments, especially during
the COVID-19 outbreak. Such recognition and detection systems significantly
improve the user experience and efficiency by providing valuable feedback. In
this paper, we propose a novel Engagement Detection with Multi-Task Training
(ED-MTT) system which minimizes mean squared error and triplet loss together to
determine the engagement level of students in an e-learning environment. The
performance of this system is evaluated and …

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