Research on Emotion Recognition Technology Driven by Deep Learning

Abstract

Facial expression analysis is a crucial tool in medical diagnosis, helping doctors better understand patients' psychological states and emotional changes. Traditional methods rely on extracting and classifying facial features from images but are often affected by noise and occlusions. To enhance accuracy and efficiency, researchers have introduced convolutional neural networks (CNNs) in deep learning, which automatically extract deep features from facial images. This approach minimizes the impact of noise and occlusion, providing more precise emotion analysis to support medical diagnosis and treatment.