计算机与数字工程2024，Vol.52Issue(1)：259-265,7.DOI:10.3969/j.issn.1672-9722.2024.01.043
一种基于改进VGG16网络的人脸表情识别算法
A Facial Expression Recognition Algorithm Based on Improved VGG16 Network
摘要
Abstract
When the neural network recognizes facial expressions,the classification loss function used is mainly the cross-en-tropy loss function,which leads to the problem that the network has a low recognition rate for different facial expression categories.The category attention mechanism and context awareness pyramid are introduced into the VGG16 network to generate a category loss function,which together with the cross-entropy loss function is used as the loss function for network training,so as to improve the accuracy of facial expression recognition of the network.The experimental results show that the improved VGG16 network has a high-er facial expression recognition rate on the facial expression datasets RAF-DB and FERPLUS than the original VGG16 network.关键词
卷积神经网络/表情识别/类别注意力/感受野Key words
convolutional neural network/facial expression recognition/category attention/feel the wild分类
信息技术与安全科学引用本文复制引用
董翠,罗晓曙,黄苑琴..一种基于改进VGG16网络的人脸表情识别算法[J].计算机与数字工程,2024,52(1):259-265,7.基金项目
广西人文社会科学发展研究中心科学研究工程·创新创业专项(重大委托项目)(编号:ZDCXCY01)资助. （重大委托项目）
