Open AccessPrediction of Autism Spectrum Disorder by Facial Recognition Using Machine Learning
Author(s) -
Srividhya Ganesan,
Raju Dr.,
Senthil J
Publication year - 2021
Publication title -
webology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.259
H-Index - 18
ISSN - 1735-188X
DOI - 10.14704/web/v18si02/web18291
Subject(s) - autism spectrum disorder , autism , artificial intelligence , support vector machine , neurodevelopmental disorder , classifier (uml) , computer science , machine learning , psychology , pattern recognition (psychology) , developmental psychology
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.