메뉴 건너뛰기




Volumn 2, Issue , 2010, Pages 976-980

Two-dimensional Sparse Principal Component Analysis: A new technique for feature extraction

Author keywords

Elastic net; Face recognition; Feature extraction; Two dimensional sparse principal component analysis

Indexed keywords


EID: 78149311430     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNC.2010.5582886     Document Type: Conference Paper
Times cited : (7)

References (11)
  • 4
    • 0036721691 scopus 로고    scopus 로고
    • From imagevector to matrix: A straightforward image projection technique-IMPCA vs. PCA
    • J. Yang and J. Y. Yang, "From imagevector to matrix: a straightforward image projection technique-IMPCA vs. PCA," Pattern Recognition, vol. 35, no. 9, pp. 1997-1999, 2002.
    • (2002) Pattern Recognition , vol.35 , Issue.9 , pp. 1997-1999
    • Yang, J.1    Yang, J.Y.2
  • 6
    • 85194972808 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • R. Tibshirani, "Regression shrinkage and selection via the lasso, "Journal of the Royal Statistical Society (B), vol. 58, no. 1, pp. 267-288, 1996.
    • (1996) Journal of the Royal Statistical Society (B) , vol.58 , Issue.1 , pp. 267-288
    • Tibshirani, R.1
  • 7
    • 16244401458 scopus 로고    scopus 로고
    • Regularization and variable selection via the elastic net
    • H. Zou and T. Hastie, "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society(B), vol. 67, no. 2, pp. 301-320, 2005.
    • (2005) Journal of the Royal Statistical Society(B) , vol.67 , Issue.2 , pp. 301-320
    • Zou, H.1    Hastie, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.