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Volumn 8232 LNCS, Issue , 2013, Pages 26-33

Non-negative sparse representation based on block NMF for face recognition

Author keywords

Block non negative matrix factorization; Face recognition; Non negative sparse representation

Indexed keywords

DISCRIMINANT POWER; FACIAL IMAGES; FEATURE FUSION; FERET FACE DATABASE; NON NEGATIVES; NONNEGATIVE MATRIX FACTORIZATION; REGULARIZED LEAST SQUARES; SPARSE REPRESENTATION;

EID: 84893120931     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-02961-0_4     Document Type: Conference Paper
Times cited : (10)

References (9)
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    • Lee, D.D.1    Seung, H.S.2
  • 2
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • Lee, D.D., Seung, H.S.: Learning the parts of objects by non-negative matrix factorization. Nature 401, 788-791 (1999)
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 3
    • 52949092365 scopus 로고    scopus 로고
    • Incremental Nonnegative Matrix Factorization for Face Recognition
    • doi:10.1155/2008/410674
    • Chen, W.S., Pan, B.B., Fang, B., Li, M., Tang, J.: Incremental Nonnegative Matrix Factorization for Face Recognition. Mathematical Problems in Engineering 2008, Article ID 410674, 17 pages (2008), doi:10.1155/2008/410674
    • (2008) Mathematical Problems in Engineering , vol.2008 , pp. 17
    • Chen, W.S.1    Pan, B.B.2    Fang, B.3    Li, M.4    Tang, J.5
  • 4
    • 22144488449 scopus 로고    scopus 로고
    • Sparse non-negative solution of underdetermined linear equations by linear programming
    • Donoho, D., Tanner, J.: Sparse non-negative solution of underdetermined linear equations by linear programming. Proc. Nat. Acad. Sci. 102(27), 9446-9451 (2005)
    • (2005) Proc. Nat. Acad. Sci. , vol.102 , Issue.27 , pp. 9446-9451
    • Donoho, D.1    Tanner, J.2
  • 5
    • 33646365077 scopus 로고    scopus 로고
    • For most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution
    • Donoho, D.: For most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution. Comm. Pure and Applied Math. 59(6), 797-829 (2006)
    • (2006) Comm. Pure and Applied Math. , vol.59 , Issue.6 , pp. 797-829
    • Donoho, D.1
  • 6
    • 55349132734 scopus 로고    scopus 로고
    • On the uniqueness of non-negative sparse solutions to underdetermined systems of equations
    • Bruckstein, A.M., Elad, M., Zibulevsky, M.: On the uniqueness of non-negative sparse solutions to underdetermined systems of equations. IEEE Trans. Inf. Theory 54(11), 4813-4820 (2008)
    • (2008) IEEE Trans. Inf. Theory , vol.54 , Issue.11 , pp. 4813-4820
    • Bruckstein, A.M.1    Elad, M.2    Zibulevsky, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.