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Volumn 9787, Issue , 2016, Pages 551-561

Online appearance manifold learning for video classification and clustering

Author keywords

Dimensionality reduction; Manifold learning; Video classification; Video data mining

Indexed keywords

CLASSIFICATION (OF INFORMATION); IMAGE CLASSIFICATION; LEARNING ALGORITHMS;

EID: 84978861807     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-42108-7_43     Document Type: Conference Paper
Times cited : (3)

References (11)
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  • 2
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    • Online learning of probabilistic appearance manifolds for video-based recognition and tracking
    • Washington, DC
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    • Lee, K.C.1    Kriegman, D.2
  • 4
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    • (2000) Science , vol.290 , Issue.5500 , pp. 2268-2269
    • Seung, H.S.1    Lee, D.D.2
  • 5
    • 0034704229 scopus 로고    scopus 로고
    • A global geometric framework for nonlinear dimensionality reduction
    • Tenenbaum, J. B., de Silva, V., Langford, J. C.: A global geometric framework for nonlinear dimensionality reduction. Science 290, 2319-2323 (2000).
    • (2000) Science , vol.290 , pp. 2319-2323
    • Tenenbaum, J.B.1    de Silva, V.2    Langford, J.C.3
  • 6
    • 33645216963 scopus 로고    scopus 로고
    • Building k-connected neighborhood graphs for isometric data embedding
    • Yang, L.: Building k-connected neighborhood graphs for isometric data embedding. IEEE Trans. Pattern Anal. Mach. Intell. 28(5), 827-831 (2006).
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    • Incremental isometric embedding of high dimensional data using connected neighborhood graphs
    • Zhao, D., Yang, L.: Incremental isometric embedding of high dimensional data using connected neighborhood graphs. IEEE Trans. Pattern Anal. Mach. Intell. 31(1), 86-98 (2009).
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    • Zhao, D.1    Yang, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.