现代信息科技2025，Vol.9Issue(4)：43-46,52,5.DOI:10.19850/j.cnki.2096-4706.2025.04.009
基于注意力机制与特征融合的表情识别方法
Expression Recognition Method Based on Attention Mechanism and Feature Fusion
摘要
Abstract
In order to improve the performance of facial expression recognition in unconstrained environments,a two-stage feature fusion expression recognition deep Convolutional Neural Network framework with embedded Attention Mechanism is studied and designed.This network framework designs and introduces multiple attention modules aimed at accurately extracting expression feature information of local image positions.Meanwhile,by constructing densely connected residual blocks,the quality of feature extraction is effectively improved and the stability of the network is enhanced.On this basis,the local features are fused with the global features extracted by the multi-scale module to obtain more discriminative expression features.The experimental results show that the proposed method exhibits good expression recognition performance on the RAF-DB dataset.关键词
表情识别/注意力机制/局部特征/特征融合Key words
expression recognition/Attention Mechanism/local feature/feature fusion分类
信息技术与安全科学引用本文复制引用
江涛,李楚贞..基于注意力机制与特征融合的表情识别方法[J].现代信息科技,2025,9(4):43-46,52,5.基金项目
广东理工学院创新强校工程科研项目(2022GKJZK004) （2022GKJZK004）
广东理工学院人工智能重点学科项目(2024KDZK001) （2024KDZK001）
广东理工学院实验教学示范中心项目(SFZX202402) （SFZX202402）
