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Volumn , Issue , 2009, Pages 389-396

Multiplicative nonnegative graph embedding

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; EMBEDDINGS; FACTORIZATION; GRAPH ALGORITHMS; INVERSE PROBLEMS; ITERATIVE METHODS; TENSORS;

EID: 70450203305     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2009.5206574     Document Type: Conference Paper
Times cited : (21)

References (15)
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    • Sparse image coding using a 3d nonnegative tensor factorization
    • T. Hazan, S. Polak, and A. Shashua. Sparse image coding using a 3d nonnegative tensor factorization. ICCV, 2005.
    • (2005) ICCV
    • Hazan, T.1    Polak, S.2    Shashua, A.3
  • 5
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by nonnegative matrix factorization
    • D. Lee and H. Seung. Learning the parts of objects by nonnegative matrix factorization. Nature, 1999.
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    • Lee, D.1    Seung, H.2
  • 6
    • 0035683536 scopus 로고    scopus 로고
    • Learning spatially localized, partsbased representation
    • S. Li, X. Hou, H. Zhang, and Q. Cheng. Learning spatially localized, partsbased representation. CVPR, 2001.
    • (2001) CVPR
    • Li, S.1    Hou, X.2    Zhang, H.3    Cheng, Q.4
  • 7
    • 34548062342 scopus 로고    scopus 로고
    • A novel discriminant nonnegative matrix factorization algorithm with applications to facial image characterization problems
    • I. Kotsia, S. Zafeiriou, and I. Pitas. A Novel Discriminant Nonnegative Matrix Factorization Algorithm With Applications to Facial Image Characterization Problems. TIFS, 2007.
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    • Kotsia, I.1    Zafeiriou, S.2    Pitas, I.3
  • 9
    • 31844432834 scopus 로고    scopus 로고
    • Nonnegative tensor factorization with applications to statistics and computer vision
    • A. Shashua and T. Hazan. Nonnegative Tensor Factorization with Applications to Statistics and Computer Vision. ICML, 2005.
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    • Shashua, A.1    Hazan, T.2
  • 10
    • 70450184578 scopus 로고    scopus 로고
    • Non-orthogonal binary subspace and its applications in computer vision
    • H. Tao, R. Crabb, and F. Tang. Non-orthogonal binary subspace and its applications in computer vision. CVPR, 2005.
    • (2005) CVPR
    • Tao, H.1    Crabb, R.2    Tang, F.3
  • 11
    • 11144327494 scopus 로고    scopus 로고
    • Fisher nonnegative matrix factorization for learning local features
    • Y. Wang, Y. Jiar, C. Hu, and M. Turk. Fisher nonnegative matrix factorization for learning local features. ACCV, 2004.
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    • Wang, Y.1    Jiar, Y.2    Hu, C.3    Turk, M.4
  • 13
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    • Graph embedding and extensions: A general framework for dimensionality reduction
    • S. Yan, D. Xu, B. Zhang, H. Zhang, Q. Yang and S. Lin. Graph Embedding and Extensions: A General Framework for Dimensionality Reduction. TPAMI, 2007.
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    • Yan, S.1    Xu, D.2    Zhang, B.3    Zhang, H.4    Yang, Q.5    Lin, S.6
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    • Two-dimensional linear discriminant analysis
    • J. Ye, R. Janardan, and Q. Li. Two-Dimensional Linear Discriminant Analysis. NIPS, 2004.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.