计算机应用与软件2024，Vol.41Issue(8)：162-167,6.DOI:10.3969/j.issn.1000-386x.2024.08.023
基于注意力改进残差网络结构的表情识别方法
FACIAL EXPRESSION RECOGNITION METHOD BASED ON MULTI-CHANNEL RESIDUAL NETWORK
摘要
Abstract
To solve the problem of insufficient feature extraction of CNN in complex images,an improved residual network based on attention is proposed for facial expression recognition.A dual stream network was designed to detect the key points while completing the coarse feature facial expression recognition,and the attention mechanism was used to increase the weight of the features around the key points.Based on the residual network model,the jump connection between residual blocks was improved,and the ordinary convolution in residual blocks was improved to block convolution to enhance the feature extraction ability.Two facial expression recognition networks were combined for classification.The experimental results show that the model scheme has better performance.关键词
人脸表情识别/残差网络/注意力机制/分组卷积Key words
Facial expression recognition/Residual network/Attention mechanism/Group convolution分类
信息技术与安全科学引用本文复制引用
张智,魏蘅..基于注意力改进残差网络结构的表情识别方法[J].计算机应用与软件,2024,41(8):162-167,6.基金项目
国家自然科学基金项目(61673304) （61673304）
国家社会科学基金重大计划项目(11&ZD189). （11&ZD189）
