A person’s facial expressions reveal a great deal about their emotional state. The field of automated facial expression recognition holds great significance in the context of Human-Computer Interaction (HCI). The Wavelet Transform Features serve as the foundation for the suggested facial emotion identification technique. As texture characteristics, the image’s grey-level co-occurrence parameters and discrete wavelet transform image properties were employed. The neuro-fuzzy Adaptive Neuro-Fuzzy Inference System (ANFIS) is used for classification. Validation of the suggested methodology’s performance yields encouraging results that demonstrate the recognition system’s efficacy.


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    Titel :

    An Efficient Neuro-Fuzzy Classification System for Identifying Emotions


    Beteiligte:
    Kavitha, S (Autor:in) / Rani, A Jaya Mabel (Autor:in)


    Erscheinungsdatum :

    06.11.2024


    Format / Umfang :

    432335 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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