Authors - Liyan Grace Shaji, Lakshmi K.S, Shazil Mohammad Iqbal, Don Basil Saj, Tom Thomas Abstract - Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects skills related to social interaction and communication. Of late, this is estimated to be prevalent in 1 among 100 children, across the world. Unfortunately, our present, diagnostic methods, like ADI-R and ADOS, rely on questionnaires, which render them to be time-consuming, expensive, and skill-dependent. Hence, to address these challenges, FaceIt is developed, which is a Deep Learning-based diagnostic tool that integrates real-time image capture and classification for rapid and accessible ASD screening. The tool efficiently processes facial images captured or uploaded by users, by performing preprocessing steps like cropping and alignment. A Convolutional Neural Network (CNN) extracts facial features to detect ASD, while a Bayesian CNN captures uncertainty in predictions. Its user-friendly interface allows self administration, devoid of professional supervision. The faster and more accessible preliminary screening even facilitates timely follow-up diagnostics if needed, thus making this an optimum solution for widespread use.
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