The mental health and well-being of children are critical components of their overall development and future success. In India, only 1 in $\mathbf{6 8}$ children are diagnosed with autism, since monitoring and addressing the mental health issues among children is a challenge because of various factors. Studies have proven that autism detection can be made possible with the assessment of specific facial features that are used as primary markers for the proposed model. The proposed solution aims to leverage technological advancements, such as deep learning, for detecting autism in children using the aforementioned markers. The model gathers data on the children’s facial features and predicts any underlying mental disorder. Since the application collects and analyzes sensitive information from the users, an additional security feature is implemented in the proposed solution using blockchain. Key features of the solution include standardized assessment tools, real-time tracking capabilities, personalized interventions, and seamless communication channels between parents, caregivers, and mental health professionals.


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    Titel :

    Autism Detection using InceptionV3 and Security using Blockchain


    Beteiligte:
    Annie Silviya, S H (Autor:in) / Seetha, R (Autor:in) / Raja, S (Autor:in) / Sriman, B (Autor:in) / Rupesh, S (Autor:in) / Gopala Krishnan, J (Autor:in)


    Erscheinungsdatum :

    06.11.2024


    Format / Umfang :

    529486 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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