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Volumn , Issue , 2011, Pages 483-490

Learning a dictionary of deformable patches using GPUs

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; DEFORMABLE TEMPLATES; DICTIONARY LEARNING; DOMAIN-SPECIFIC KNOWLEDGE; HANDWRITTEN DIGIT; PARALLEL FRAMEWORK; RECOGNITION PERFORMANCE; SEARCH SPACES; SHAPE RECOGNITION; SIMPLE METHOD; SPARSE REPRESENTATION;

EID: 84856632169     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCVW.2011.6130282     Document Type: Conference Paper
Times cited : (5)

References (23)
  • 5
    • 0042004575 scopus 로고    scopus 로고
    • Class specific top-down segmentation
    • E. Borenstein and S. Ullman. Class specific top-down segmentation. In ECCV, 2002.
    • (2002) ECCV
    • Borenstein, E.1    Ullman, S.2
  • 6
    • 77955993281 scopus 로고    scopus 로고
    • Learning midlevel features for recognition
    • Y. Boureau, F. Bach, Y. LeCun, and J. Ponce. Learning midlevel features for recognition. In CVPR, 2010.
    • (2010) CVPR
    • Boureau, Y.1    Bach, F.2    Lecun, Y.3    Ponce, J.4
  • 8
    • 78649603618 scopus 로고    scopus 로고
    • Image quilting for texture synthesis and transfer
    • A. A. Efros and W. T. Freeman. Image quilting for texture synthesis and transfer. In SIGGRAPH, 2001.
    • (2001) SIGGRAPH
    • Efros, A.A.1    Freeman, W.T.2
  • 9
    • 84856657483 scopus 로고    scopus 로고
    • Hierarchical features for object classification
    • B. Epshtein and S. Ullman. Hierarchical features for object classification. In ICCV, 2005.
    • (2005) ICCV
    • Epshtein, B.1    Ullman, S.2
  • 10
    • 85170282443 scopus 로고    scopus 로고
    • A density-based algorithm for discovering clusters in large spatial databases with noise
    • M. Ester, H. Kriegel, J. Sander, and X. Xu. A density-based algorithm for discovering clusters in large spatial databases with noise. In KDD, page 226 231, 1996.
    • (1996) KDD , pp. 226-231
    • Ester, M.1    Kriegel, H.2    Sander, J.3    Xu, X.4
  • 11
    • 35148867545 scopus 로고    scopus 로고
    • Towards scalable representation of object categories: Learning a hierarchy of parts
    • S. Fidler and A. Leonardis. Towards scalable representation of object categories: Learning a hierarchy of parts. In CVPR, 2007.
    • (2007) CVPR
    • Fidler, S.1    Leonardis, A.2
  • 13
    • 33751577170 scopus 로고    scopus 로고
    • Tangent distant kernels for support vector machines
    • B. Haasdonk and D. Keysers. Tangent distant kernels for support vector machines. In ICPR, 2002.
    • (2002) ICPR
    • Haasdonk, B.1    Keysers, D.2
  • 14
    • 33745805403 scopus 로고    scopus 로고
    • A fast learning algorithm for deep belief nets
    • G. E. Hinton, S. Osindero, and Y. W. Teh. A fast learning algorithm for deep belief nets. Neural Computation, 18(7):1527-1554, 2006.
    • (2006) Neural Computation , vol.18 , Issue.7 , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2    Teh, Y.W.3
  • 15
    • 77953183471 scopus 로고    scopus 로고
    • What is the best multi-stage architecture for object recognition?
    • K. Jarrett, K. Kavukcuoglu, M. Ranzato, and Y. LeCun. What is the best multi-stage architecture for object recognition? In ICCV, 2009.
    • (2009) ICCV
    • Jarrett, K.1    Kavukcuoglu, K.2    Ranzato, M.3    Lecun, Y.4
  • 17
    • 71149119164 scopus 로고    scopus 로고
    • Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
    • H. Lee, R. Grosse, R. Ranganath, and A. Ng. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. In ICML, 2009.
    • (2009) ICML
    • Lee, H.1    Grosse, R.2    Ranganath, R.3    Ng, A.4
  • 19
    • 0029938380 scopus 로고    scopus 로고
    • Emergence of simple-cell receptive field properties by learning a sparse code for natural images
    • B. A. Olshausen and D. J. Field. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381:607-609, 1996.
    • (1996) Nature , vol.381 , pp. 607-609
    • Olshausen, B.A.1    Field, D.J.2
  • 20
    • 51949106645 scopus 로고    scopus 로고
    • Selftaught learning: Transfer learning from unlabeled data
    • R. Raina, A. Battle, H. Lee, B. Packer, and A. Ng. Selftaught learning: Transfer learning from unlabeled data. In ICML, 2007.
    • (2007) ICML
    • Raina, R.1    Battle, A.2    Lee, H.3    Packer, B.4    Ng, A.5
  • 21
    • 34948870900 scopus 로고    scopus 로고
    • Unsupervised learning of invariant feature hierarchies with applications to object recognition
    • M. Ranzato, F. Huang, Y. Boureau, and Y. LeCun. Unsupervised learning of invariant feature hierarchies with applications to object recognition. In CVPR, 2007.
    • (2007) CVPR
    • Ranzato, M.1    Huang, F.2    Boureau, Y.3    Lecun, Y.4
  • 22
    • 50949122572 scopus 로고    scopus 로고
    • Deformable template as active basis
    • Y. N. Wu, Z. Si, C. Fleming, and S. Zhu. Deformable template as active basis. In ICCV, 2007.
    • (2007) ICCV
    • Wu, Y.N.1    Si, Z.2    Fleming, C.3    Zhu, S.4
  • 23
    • 77955995797 scopus 로고    scopus 로고
    • Part and appearance sharing: Recursive compositional models for multi-view multi-object detection
    • L. Zhu, Y. Chen, A. Torralba, W. Freeman, and A. Yuille. Part and appearance sharing: Recursive compositional models for multi-view multi-object detection. In CVPR, 2010.
    • (2010) CVPR
    • Zhu, L.1    Chen, Y.2    Torralba, A.3    Freeman, W.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.