工矿自动化2018，Vol.44Issue(5)：95-100,6.DOI:10.13272/j.issn.1671-251x.17312
基于卷积神经网络的矿工面部表情识别方法
Miners' facial expression recognition method based on convolutional neural network
摘要
Abstract
In view of problems of low recognition rate and complex algorithm of traditional miner's facial expression recognition methods,based on convolutional neural network and combining with nonlinear mapping function in support vector machine algorithm,a miners' facial expression recognition method based on convolutional neural network was proposed.The convolutional neural network adopts sharing weights strategy,constructs convolutional layer directly with fixed weights,and determine network hierarchy according to matching growth rules.Preprocessed miner's facial expression images are used as test set and training sets of the convolutional neural network.Supportive vector machine is used to classify neurons that represent miner's facial expression features,so as to realize classification and recognition of miner's facial expressions.The experimental results show that the recognition rate of miner's facial expression of the proposed method reaches 90.71％,which can meet the practical application needs.关键词
矿工面部表情识别/卷积神经网络/支持向量机/权值共享策略/匹配生长规则Key words
miner's facial expression recognition/convolutional neural network/support vector machine/weight sharing strategy/matching growth rule分类
矿业与冶金引用本文复制引用
杜云,张璐璐,潘涛..基于卷积神经网络的矿工面部表情识别方法[J].工矿自动化,2018,44(5):95-100,6.基金项目
国家重点研发计划项目(2016YFC0801800). （2016YFC0801800）
