四川师范大学学报（自然科学版）2025，Vol.48Issue(3)：383-391,9.DOI:10.3969/j.issn.1001-8395.2025.03.009
基于改进VGG16网络的失能老人表情识别研究
Research on Expression Recognition of Disabled Elderly People Based on Improved VGG16 Network
摘要
Abstract
In order to better monitor the emotional state of elderly individuals with disabilities,this article employs VGG16 as the foundational model for emotion recognition and makes improvements upon it.Firstly,the activation function is replaced with the SiLU function and batch normalization layers are added at the feature-extraction level.Secondly,adaptive average pooling is utilized in the classification layer to process images,while convolutional layers are used to achieve fully connected effects,thereby avoiding issues re-lated to excessive parameters and overfitting.Lastly,through the attention mechanism of the SENet channel,convolutional layers with the same number of channels are iteratively fused to enable interaction between shallow and deep features,enriching the feature extrac-tion of the facial expression.The experimental results indicate that the recognition accuracy on the FER2013 and CK+datasets reached 72.50%and 98.70%,respectively,which represents an improvement of 8.20%and 3.90%compared to the baseline meth-od.These findings demonstrate that the improved method can enhance emotion-recognition rates and possesses certain advancements.关键词
VGG16/表情识别/自适应平均化/通道注意力机制Key words
VGG16 model/expression recognition/adaptive averaging/channel attention mechanism分类
计算机与自动化引用本文复制引用
何巍,李苏..基于改进VGG16网络的失能老人表情识别研究[J].四川师范大学学报（自然科学版）,2025,48(3):383-391,9.基金项目
国家自然科学基金青年基金(62301348) （62301348）
