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An Intelligent Online Attendance Tracking System Through Facial Recognition Technique Using Edge Computing
2nd International Conference on Intelligent and Cloud Computing, ICICC 2021 ; 286:3-15, 2022.
Article in English | Scopus | ID: covidwho-1826293
ABSTRACT
Recently, due to COVID-19 pandemic, the classes, seminars, meetings are scheduled on virtual platform. It is a need to keep track of the presence of attendees. Earlier online attendance involved extracting the list of attendees, which was inconvenient as a lot of people mute themselves and leave the meeting altogether. Therefore, a tool is required to capture attendance through facial recognition which can effectively identify the attendees who remain online for the whole duration of the lecture. In this paper, a method has been proposed to completely automate the attendance tracking system using the concept of edge computing. The tool runs alongside any video conference platform and tracks the faces of attendees in a random interval, and using face recognition technique, find out the people who remain present for the complete duration of the class. This novel method acts as a fail-proof method to monitor attendance and improve digital transparency. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Randomized controlled trials Language: English Journal: 2nd International Conference on Intelligent and Cloud Computing, ICICC 2021 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Randomized controlled trials Language: English Journal: 2nd International Conference on Intelligent and Cloud Computing, ICICC 2021 Year: 2022 Document Type: Article