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《Journal of Xiamen University(Natural Science)》 2019-01
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Face recognition using local strengthen least-square regression classification method

JIAN Cairen;XIA Jingbo;School of Information Science & Technology,Xiamen University Tan Kah kee College;  
In order to improve the weakness of classification method based on the representation theory that ignore the influence of noise on the reconstruction coefficients,we propose a local strengthen least-square regression classification method to improve the least-square regression classification method by using the local-constraint cooperative representation.The proposed method can select neighbor samples adaptively by using nonnegative sparse representation.It strengthens reconstruction coefficients by using neighbor data samples,and improves anti-noise ability.Furthermore,it can overcome the over-fitting problems that plague traditional classification methods.Experimental results on the four face recognition datasets show that this method can improve recognition accuracies.
【Fund】: 福建省自然科学基金(2018J01101)
【CateGory Index】: TP391.41
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【Citations】
Chinese Journal Full-text Database 1 Hits
1 JIAN Cairen;CHEN Xiaoyun;College of Mathematics and Computer Science,Fuzhou University;Tan Kah Kee Colleage,Xiamen University;;Gene expression data classification model based on sparse representation and least square regression[J];福州大学学报(自然科学版);2015-06
【Secondary Citations】
Chinese Journal Full-text Database 1 Hits
1 YANG Fan~1,LIN Chen~2,ZHOU Qi-feng~1,FU Chang-hong~1,LUO Lin-kai~1 (1.Department of Automation,Xiamen University,Xiamen 361005,China; 2.Department of Computer Science,Xiamen University,Xiamen 361005,China);Random forest based potential k nearest neighbor classifier and its application in gene expression data[J];系统工程理论与实践;2012-04
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