现代信息科技2024，Vol.8Issue(8)：102-105,110,5.DOI:10.19850/j.cnki.2096-4706.2024.08.023
基于注意力机制的表情识别改进方法
An Improved Method for Facial Expression Recognition Based on Attention Mechanism
摘要
Abstract
Targeting the problems of poor recognition accuracy and a large number of Deep Learning model parameters due to light and posture influence in facial expression recognition,this paper proposes an improved Convolutional Neural Network model based on Attention Mechanism.Through the introduction of the Attention Mechanism module,the model selectively focuses on the locally important information of the target object and reduces the interference of irrelevant information,while using a neural network with fewer neurons and a large convolutional kernel,the parameters of the network are significantly decreased,and the method builds a lightweight Convolutional Neural Network model with a shallower hierarchy and fewer parameters.Experiments are conducted on the CK+facial expression dataset,and results show that the proposed method significantly reduces model parameters while ensuring facial recognition accuracy,with an accuracy rate of 96.37%.关键词
人脸表情识别/注意力机制/卷积神经网络/深度学习Key words
facial expression recognition/Attention Mechanism/Convolutional Neural Network/Deep Learning分类
信息技术与安全科学引用本文复制引用
徐梦阳..基于注意力机制的表情识别改进方法[J].现代信息科技,2024,8(8):102-105,110,5.
