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Boosting in random subspace for face recognition
Gao, Yong; Wang, Yangsheng; Huang, DS; Li, K; Irwin, GW
Source PublicationINTELLIGENT COMPUTING IN SIGNAL PROCESSING AND PATTERN RECOGNITION
2006
Volume345Pages:172-181
SubtypeArticle
AbstractBoosting is a general method for improving the performance of any learning algorithm. In this paper, an unusual regularization technique, boosting in random subspace, is employed to improve generalization capability of boosting. Meanwhile the space complexity of training is lowered, and the classifier combination strategy can be used to further improve recognition accuracy. Using the method, we achieved 98.99% rank-1 recognition rate on FERET fb probe set.
WOS HeadingsScience & Technology ; Technology
Indexed ByISTP ; SCI
Language英语
WOS Research AreaAutomation & Control Systems ; Computer Science ; Engineering
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS IDWOS:000240385300018
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9304
Collection09年以前成果
AffiliationChinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Gao, Yong,Wang, Yangsheng,Huang, DS,et al. Boosting in random subspace for face recognition[J]. INTELLIGENT COMPUTING IN SIGNAL PROCESSING AND PATTERN RECOGNITION,2006,345:172-181.
APA Gao, Yong,Wang, Yangsheng,Huang, DS,Li, K,&Irwin, GW.(2006).Boosting in random subspace for face recognition.INTELLIGENT COMPUTING IN SIGNAL PROCESSING AND PATTERN RECOGNITION,345,172-181.
MLA Gao, Yong,et al."Boosting in random subspace for face recognition".INTELLIGENT COMPUTING IN SIGNAL PROCESSING AND PATTERN RECOGNITION 345(2006):172-181.
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