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Home / Archives / Volume-2 / Issue-3 / Article-4

Volume - 2 | Issue - 3 | september 2020

Evaluation of Activity Monitoring Algorithm based on Smart Approaches
Pages: 175-181
Full Article PDF pdf-white-icon
DOI
10.36548/jei.2020.3.004
Published
03 August, 2020
Abstract

Activity monitoring in online group meetings has become a needed application in the COVID-19 situation. During the lockdown period, most of the teaching classes were conducted through online web applications. The number of attendees in such classes are very higher and it is not to be manageable by a single tutor of the class. The applications are also designed to show only several number of person's faces in a particular window. To improve the quality of such online classes, it is mandatory to verify the listener's activity. The paper evaluates certain artificial intelligence based deep learning techniques for finding a suitable approach for monitoring the listener's activity in real time.

Keywords

Facial emotion detection deep learning classification class monitoring algorithm group meeting emotion detection

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