Facial Feature Classification for Children with Autism Based on Convolutional Neural Networks
Autism in children is a difficult disease to detect early.If this symptom is not treated in time,it will affect the whole life.Therefore,early detection and treatment are of great significance.The traditional diagnosis method of autism in children is usually through observation,which is labor-intensive and prone to miss the best treatment period.This paper proposes a Convolutional Neu-ral Network-based classification model for autism in children.The model takes the feature-enhanced data after image processing op-erations such as Gamma transformation and boundary enhancement as input,and achieves the classification of autism patients through the facial features of children.The experimental results show that the model has good classification performance.
Autism in childrenConvolutional Neural Networkimage processing
万方数据
维普
