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Volumn 9780521887380, Issue , 2009, Pages 241-256

Learning compositional models for object categories from small sample sets

Author keywords

[No Author keywords available]

Indexed keywords

FORMAL LANGUAGES; PROGRAMMED CONTROL SYSTEMS;

EID: 57149138691     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1017/CBO9780511635465.014     Document Type: Chapter
Times cited : (7)

References (33)
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    • Dickinson, S.1    Pentland, A.2    Rosenfeld, A.3
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    • Pictorial structures for object recognition
    • Felzenszwalb P, Huttenlocher D. 2005. Pictorial structures for object recognition. Int J Comput Vision 61(1): 55–79.
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    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
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    • 62349137210 scopus 로고    scopus 로고
    • A stochastic graph grammar for compositional object representation and recognition
    • Lin L, Wu T, Porway J, Xu Z. 2009. A stochastic graph grammar for compositional object representation and recognition. Under review for Pattern Recognition.
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    • Lin, L.1    Wu, T.2    Porway, J.3    Xu, Z.4
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    • Distinctive image features from scale-invariant keypoints
    • Lowe DG. 2004. Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2): 91–110.
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    • Tu Z. 2005. Probabilistic boosting tree: learning discriminative models for classification, recognition, and clustering. In Proceedings of the international conference on computer vision, vol 2, 1589– 1596.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.