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Volumn 3954 LNCS, Issue , 2006, Pages 308-320

Extending kernel Fisher discriminant analysis with the weighted pairwise Chernoff criterion

Author keywords

[No Author keywords available]

Indexed keywords

DATA PROCESSING; DATA REDUCTION; FACE RECOGNITION; IMAGING TECHNIQUES; NONLINEAR SYSTEMS; REAL TIME SYSTEMS;

EID: 33745820770     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11744085_24     Document Type: Conference Paper
Times cited : (7)

References (27)
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    • Kumar, N.1    Andreou, A.G.2
  • 3
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    • Linear dimensionality reduction via a heteroscedastic extension of LDA: The Chernoff criterion
    • June
    • M. Loog and R.P.W. Duin. Linear dimensionality reduction via a heteroscedastic extension of LDA: the Chernoff criterion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(6):32-739, June 2004.
    • (2004) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.26 , Issue.6 , pp. 32-739
    • Loog, M.1    Duin, R.P.W.2
  • 8
    • 10644221106 scopus 로고    scopus 로고
    • Uncorrelatecl heteroscedastic LDA based on the weighted pairwise Chernoff criterion
    • A.K. Qin, P.N. Suganthan, and M. Loog. Uncorrelatecl heteroscedastic LDA based on the weighted pairwise Chernoff criterion. Pattern Recognition, 2005.
    • (2005) Pattern Recognition
    • Qin, A.K.1    Suganthan, P.N.2    Loog, M.3
  • 10
    • 0034300875 scopus 로고    scopus 로고
    • A new LDA-based face recognition system which can solve the small sample size problem
    • L.F. Chen, H.Y.M. Liao, M.T. Ko, J.C. Lin, and G.J. Yu. A new LDA-based face recognition system which can solve the small sample size problem. Pattern Recognition, 33:1713-1726, 2000.
    • (2000) Pattern Recognition , vol.33 , pp. 1713-1726
    • Chen, L.F.1    Liao, H.Y.M.2    Ko, M.T.3    Lin, J.C.4    Yu, G.J.5
  • 11
    • 0001765951 scopus 로고    scopus 로고
    • A direct LDA algorithm for high-dimensional data with application to face recognition
    • H. Yu and J. Yang. A direct LDA algorithm for high-dimensional data with application to face recognition. Pattern Recognition, 34:2067-2070, 2001.
    • (2001) Pattern Recognition , vol.34 , pp. 2067-2070
    • Yu, H.1    Yang, J.2
  • 13
    • 0036487285 scopus 로고    scopus 로고
    • Why can LDA be performed in PCA transformed space?
    • J. Yang and J.Y. Yang. Why can LDA be performed in PCA transformed space? Pattern Recognition, 36:563-566, 2003.
    • (2003) Pattern Recognition , vol.36 , pp. 563-566
    • Yang, J.1    Yang, J.Y.2
  • 15
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • B. Schölkopf, A. Smola, and K.R. Müller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10:1299-1319, 1999.
    • (1999) Neural Computation , vol.10 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.2    Müller, K.R.3
  • 17
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    • Generalized discriminant analysis using a kernel approach
    • G. Baudat and F. Anouar. Generalized discriminant analysis using a kernel approach. Neural Computation, 12:2385-2404, 2000.
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    • Baudat, G.1    Anouar, F.2
  • 19
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    • Nonlinear discriminant analysis using kernel functions and the generalized singular value decomposition
    • to appear
    • C.H. Park and H. Park. Nonlinear discriminant analysis using kernel functions and the generalized singular value decomposition. SIAM Journal on Matrix Analysis and Application, to appear (http://www-users.cs.umn.edu/hpark/pub.html).
    • SIAM Journal on Matrix Analysis and Application
    • Park, C.H.1    Park, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.