Automated emotion identification through facial expression analysis is a compelling research topic with numerous applications in safety, health, and human-machine interactions. Researchers aim to develop techniques to analyze and extract facial movements to improve predictive models using deep learning architectures. With the increasing popularity of online education, teachers must be aware of their students' emotional condition, which can affect their ability to determine if students understand the lessons. This study seeks to bridge this void by furnishing educators with insights into their students' emotions using deep learning models concentrating on facial characteristics and identifying emotions. The proposed model adeptly detects emotions and produces valuable reports for the assessment procedure.


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    Titel :

    Enhancing Online Learning with Automated Emotion Identification using Facial Expressions


    Beteiligte:
    Jagadeesh, M. (Autor:in) / L, Zubair Ali. (Autor:in) / S, Vishnu. (Autor:in) / Sajeev, Nandita (Autor:in) / N, Nithish Kumar (Autor:in)


    Erscheinungsdatum :

    22.11.2023


    Format / Umfang :

    704652 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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