Prediction of Autism Spectrum Disorder by Facial Recognition Using Machine Learning

Abstract

Autism is normally characterized as pervading disorder. The role Pervasive implies that the disorder is acute. Autism spectrum disorder (ASD) individuals face difficulties in interacting with others. They also have a problem in responding to the actions, hyperactive and behavioural issues. There have been numerous technological enhancements in prediction of autism traits. This paper focusses on various machine learning methods to classify an autistic child. It mainly focusses on classification models applying VGG16 algorithm of SVM classifier, CNN and Haar Cascade using OpenCV. Using these models, better accuracy was achieved compared to other models of classification.

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