Year: 2025
Type: article
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.
Authors: Xiaoyan He, Honghu Zhang, Zhiguo Zhang, Xiaopeng Wang
Institution: Taiyuan University of Technology
Language: English
Topic: Emotion and Mood Recognition
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4412818966