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Volumn 1, Issue , 2011, Pages 411-416

Latent semantic learning by efficient sparse coding with hypergraph regularization

Author keywords

[No Author keywords available]

Indexed keywords

ACTION RECOGNITION; DATA SETS; HIGH-LEVEL FEATURES; HISTOGRAM INTERSECTION KERNELS; HYPERGRAPH; LARGE VOCABULARY; LATENT SEMANTIC ANALYSIS; LATENT SEMANTICS; MID-LEVEL FEATURES; SPARSE CODING; TOPIC MODEL; YOUTUBE;

EID: 80055058096     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (12)

References (17)
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  • 3
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    • Cao, L.1    Tian, Y.2    Liu, Z.3    Yao, B.4    Zhang, Z.5    Huang, T.6
  • 5
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    • Learning a hierarchy of discriminative space-time neighborhood features for human action recognition
    • Kovashka, A., and Grauman, K. 2010. Learning a hierarchy of discriminative space-time neighborhood features for human action recognition. In Proc. CVPR, 2046-2053.
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    • Lafon, S.1    Lee, A.B.2
  • 9
    • 51949085157 scopus 로고    scopus 로고
    • Learning human actions via information maximization
    • Liu, J., and Shah, M. 2008. Learning human actions via information maximization. In Proc. CVPR, 1-8.
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    • Liu, J.1    Shah, M.2
  • 10
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    • Recognizing realistic actions from videos in the wild
    • Liu, J.; Luo, J.; and Shah, M. 2009. Recognizing realistic actions from videos in the wild. In Proc. CVPR, 1996-2003.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.