计算机与数字工程2023，Vol.51Issue(10)：2425-2430,6.DOI:10.3969/j.issn.1672-9722.2023.10.039
基于DenseNet的人脸表情识别方法研究
Research on Human Facial Expression Recognition Method Based on DenseNet
顾状状 1许学斌 1路龙宾 1豆阳光2
作者信息
- 1. 西安邮电大学计算机学院 西安 710000
- 2. 长安大学地质工程与测绘学院 西安 710054
- 折叠
摘要
Abstract
In the face recognition field,this paper proposes a human facial expression recognition method based on dense con-volutional neural network.The method achieves efficient feature expression with low computing resources through feature reuse and bypass connection strategy,so as to improve the accuracy of facial expression recognition system.The human facial expression recog-nition method proposed in this paper uses GPU computing to continuously research and optimize the model,and finally it achieves 96.88%accuracy on the human facial expression database which is composed with KDEF dataset and the human facial expression dataset produced in the article,which is better than the most of the current published human facial expression recognition methods.This paper uses the pre-trained facial expression recognition model to design the prototype software of facial expression recognition,which can achieve good recognition accuracy by using the camera to capture facial expression in real time.关键词
稠密卷积神经网络/人脸表情识别/深度学习/图像分类Key words
DenseNet/facial expression recognition/deep learning/image classification分类
信息技术与安全科学引用本文复制引用
顾状状,许学斌,路龙宾,豆阳光..基于DenseNet的人脸表情识别方法研究[J].计算机与数字工程,2023,51(10):2425-2430,6.
