Research on Emotion Recognition Technology Driven by Deep Learning

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.

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Publication Details

Journal
Advances in Engineering Technology Research
Published
2025-05-29
DOI
https://doi.org/10.56028/aetr.14.1.106.2025
Primary Topic
Advanced Computing and Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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Research on Emotion Recognition Technology Driven by Deep Learning

Honghu Zhang, Xiaopeng Wang, Xiaoyan He, Zhiguo Zhang
Advances in Engineering Technology Research
Advanced Computing and Algorithms
article

Research on Emotion Recognition Technology Driven by Deep Learning

Honghu Zhang, Xiaopeng Wang, Xiaoyan He, Zhiguo Zhang
article en

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.

Advances in Engineering Technology ResearchVol. 14(1)
Openalex Percentile: Top 75%
Advanced Computing and Algorithms
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