Zhengyin Ding

Abstract Automated assessment through the analysis of facial expressions in autism can assist in early screening, providing strong support for timely intervention and contributing to the healthy development of patients. However, current deep learning models still face several challenges in the practical application of intelligent diagnosis for Autism Spectrum Disorder (ASD). First, traditional models struggle to fully capture subtle facial expression changes and local fine-grained features.