A fundamental system necessary for monitoring student performance is attendance tracking. It is always a harder task to monitor the student consistently all through the learning period. A conventional based attendance system is not efficient enough, as it tracks the student's presence at the start or the end of the hour. This research work has proposed a facial recognition and artificial intelligence (AI)-based attendance tracking system. The proposed system includes a face recognition model to recognize real time images and upload the data to cloud server by using a deep learning TensorFlow framework. As a part of the proposed attendance tracking system, the face recognition system can also be utilized to maintain “punch card” records. It can be used to enhance recognition, authentication and security.


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    Titel :

    AI-based Attendance Tracking System using Real-Time Facial Recognition


    Beteiligte:
    Abirami, S.K. (Autor:in) / Jyothikamalesh, S. (Autor:in) / Sowmiya, M. (Autor:in) / Abirami, S. (Autor:in) / Angel Latha Mary, S. (Autor:in) / Jayasudha, C. (Autor:in)


    Erscheinungsdatum :

    01.12.2022


    Format / Umfang :

    579507 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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