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Volumn 115, Issue 11, 2015, Pages 812-816

Combined supervised information with PCA via discriminative component selection

Author keywords

Algorithms; Design of algorithms; Face recognition; Linear Discriminant Analysis (LDA); Multivariate statistic analysis; Principal Component Analysis (PCA)

Indexed keywords

ALGORITHMS; DISCRIMINANT ANALYSIS; FACE RECOGNITION; MULTIVARIANT ANALYSIS;

EID: 84935034277     PISSN: 00200190     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ipl.2015.06.010     Document Type: Article
Times cited : (13)

References (15)
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    • Turk, M.1    Pentland, A.2
  • 4
    • 80052768748 scopus 로고    scopus 로고
    • Improve robustness of sparse PCA by L 1-norm maximization
    • D. Meng, Q. Zhao, and Z. Xu Improve robustness of sparse PCA by L 1-norm maximization Pattern Recognit. 45 1 2012 487 497
    • (2012) Pattern Recognit. , vol.45 , Issue.1 , pp. 487-497
    • Meng, D.1    Zhao, Q.2    Xu, Z.3
  • 5
    • 27844508580 scopus 로고    scopus 로고
    • Class-information-incorporated principal component analysis
    • S. Chen, and T. Sun Class-information-incorporated principal component analysis Neurocomputing 69 1 2005 216 223
    • (2005) Neurocomputing , vol.69 , Issue.1 , pp. 216-223
    • Chen, S.1    Sun, T.2
  • 10
    • 33947416035 scopus 로고    scopus 로고
    • Near-optimal signal recovery from random projections: universal encoding strategies?
    • E.J. Candes, and T. Tao Near-optimal signal recovery from random projections: universal encoding strategies? IEEE Trans. Inf. Theory 52 12 2006 5406 5425
    • (2006) IEEE Trans. Inf. Theory , vol.52 , Issue.12 , pp. 5406-5425
    • Candes, E.J.1    Tao, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.