Autism Spectrum Disorder Classification Using Deep Learning

<p class="0abstract">The goal of this paper is to evaluate the deep learning algorithm for people placed in Autism Spectrum Disorder (ASD) classification. ASD a developmental disability that causes affected have significant communication, social, and behavioural challenges. People with autism are saddled communication problems, difficulties social interaction displaying repetitive behaviours. Several methods been used classify from non-ASD people. However, there need explore more algorithms can yield better classification performance. Recently, significantly sharpened cutting edge wide range artificial intelligence tasks. These tasks refer object detection, speech recognition, machine translation. In research, convolutional neural network (CNN) employed. This find processes higher level accuracy. The image data pre-processed; CNN then applied non-ASD, steps implementing clearly stated. Finally, effectiveness evaluated based on accuracy support vector (SVM) utilised purpose comparison. produces results an 97.07%, compared SVM algorithm. future, different types be applied, datasets tested hyper-parameters produce accurate classifications.</p>