{"title":"基于共轭梯度极值学习机的面部表情识别","authors":"Jian Chen","doi":"10.1117/12.2540969","DOIUrl":null,"url":null,"abstract":"This paper proposed a face recognition algorithm based on conjugate gradient extreme learning machine. General extreme learning machine algorithm, which is gained by using method of calculating generalized inverse, the process is a large amount of computation and memory consumption. For this problem, this paper proves the positive definiteness of the calculated matrix, and based on this, an extreme learning machine solution algorithm based on conjugate gradient algorithm was proposed and kernel function is introduced to improve its nonlinear classification performance. At the same time, DAG method is used to extend the binary classification conjugate gradient extreme learning machine to multi-classification problems. Experimental results show that the computational speed of the algorithm in this paper is faster than that of the general extreme learning machine algorithm, and the classification accuracy is higher than that of the general extreme learning machine algorithm.","PeriodicalId":90079,"journal":{"name":"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging","volume":"14 1","pages":"111980I - 111980I-8"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Facial expression recognition based on conjugate gradient extreme learning machine\",\"authors\":\"Jian Chen\",\"doi\":\"10.1117/12.2540969\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposed a face recognition algorithm based on conjugate gradient extreme learning machine. General extreme learning machine algorithm, which is gained by using method of calculating generalized inverse, the process is a large amount of computation and memory consumption. For this problem, this paper proves the positive definiteness of the calculated matrix, and based on this, an extreme learning machine solution algorithm based on conjugate gradient algorithm was proposed and kernel function is introduced to improve its nonlinear classification performance. At the same time, DAG method is used to extend the binary classification conjugate gradient extreme learning machine to multi-classification problems. Experimental results show that the computational speed of the algorithm in this paper is faster than that of the general extreme learning machine algorithm, and the classification accuracy is higher than that of the general extreme learning machine algorithm.\",\"PeriodicalId\":90079,\"journal\":{\"name\":\"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging\",\"volume\":\"14 1\",\"pages\":\"111980I - 111980I-8\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2540969\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2540969","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Facial expression recognition based on conjugate gradient extreme learning machine
This paper proposed a face recognition algorithm based on conjugate gradient extreme learning machine. General extreme learning machine algorithm, which is gained by using method of calculating generalized inverse, the process is a large amount of computation and memory consumption. For this problem, this paper proves the positive definiteness of the calculated matrix, and based on this, an extreme learning machine solution algorithm based on conjugate gradient algorithm was proposed and kernel function is introduced to improve its nonlinear classification performance. At the same time, DAG method is used to extend the binary classification conjugate gradient extreme learning machine to multi-classification problems. Experimental results show that the computational speed of the algorithm in this paper is faster than that of the general extreme learning machine algorithm, and the classification accuracy is higher than that of the general extreme learning machine algorithm.