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Volumn , Issue , 2011, Pages

Learning a tree of metrics with disjoint visual features

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; FORESTRY; PERSONNEL TRAINING; SEMANTICS;

EID: 85162445667     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (58)

References (37)
  • 2
    • 85067032737 scopus 로고    scopus 로고
    • On feature combination for multiclass object classification
    • P. Gehler and S. Nowozin. On feature combination for multiclass object classification. In ICCV, 2009.
    • (2009) ICCV
    • Gehler, P.1    Nowozin, S.2
  • 3
    • 70450209196 scopus 로고    scopus 로고
    • Linear spatial pyramid matching using sparse coding for image classification
    • J. Yang, K. Yu, Y. Gong, and T. Huang. Linear spatial pyramid matching using sparse coding for image classification. In CVPR, 2009.
    • (2009) CVPR
    • Yang, J.1    Yu, K.2    Gong, Y.3    Huang, T.4
  • 4
    • 85162513516 scopus 로고    scopus 로고
    • Object bank: A high-level image representation for scene classification and semantic feature sparsification
    • L.-J. Li, H. Su, E. Xing, and L. Fei-Fei. Object bank: A high-level image representation for scene classification and semantic feature sparsification. In NIPS, 2010.
    • (2010) NIPS
    • Li, L.-J.1    Su, H.2    Xing, E.3    Fei-Fei, L.4
  • 5
    • 85162037528 scopus 로고    scopus 로고
    • Factorized latent spaces with structured sparsity
    • Y. Jia, M. Salzmann, and T. Darrell. Factorized latent spaces with structured sparsity. In NIPS, 2010.
    • (2010) NIPS
    • Jia, Y.1    Salzmann, M.2    Darrell, T.3
  • 6
    • 85158044173 scopus 로고    scopus 로고
    • Image retrieval and classification using local distance functions
    • A. Frome, Y. Singer, and J. Malik. Image retrieval and classification using local distance functions. In NIPS, 2006.
    • (2006) NIPS
    • Frome, A.1    Singer, Y.2    Malik, J.3
  • 7
    • 50649091160 scopus 로고    scopus 로고
    • An invariant large margin nearest neighbour classifier
    • P. Kumar, P. Torr, and A. Zisserman. An invariant large margin nearest neighbour classifier. In ICCV, 2007.
    • (2007) ICCV
    • Kumar, P.1    Torr, P.2    Zisserman, A.3
  • 8
    • 51949104743 scopus 로고    scopus 로고
    • Fast image search for learned metrics
    • P. Jain, B. Kulis, and K. Grauman. Fast image search for learned metrics. In CVPR, 2008.
    • (2008) CVPR
    • Jain, P.1    Kulis, B.2    Grauman, K.3
  • 9
    • 79951945041 scopus 로고    scopus 로고
    • Local distance functions: A taxonomy, new algorithms, and an evaluation
    • D. Ramanan and S. Baker. Local distance functions: A taxonomy, new algorithms, and an evaluation. In PAMI, 2011.
    • (2011) PAMI
    • Ramanan, D.1    Baker, S.2
  • 10
    • 79958794518 scopus 로고    scopus 로고
    • Image-to-class distance metric learning for image classification
    • Z. Wang, Y. Hu, and L.-T. Chia. Image-to-class distance metric learning for image classification. In ECCV, 2010.
    • (2010) ECCV
    • Wang, Z.1    Hu, Y.2    Chia, L.-T.3
  • 11
    • 61749090884 scopus 로고    scopus 로고
    • Distance metric learning for large margin nearest neighbor classification
    • June
    • K. Q.Weinberger and K. L. Saul. Distance metric learning for large margin nearest neighbor classification. JMLR, 10:207-244, June 2009.
    • (2009) JMLR , vol.10 , pp. 207-244
    • Weinberger, K.Q.1    Saul, K.L.2
  • 12
    • 77955999185 scopus 로고    scopus 로고
    • Constructing category hierarchies for visual recognition
    • M. Marszalek and C. Schmid. Constructing category hierarchies for visual recognition. In ECCV, 2008.
    • (2008) ECCV
    • Marszalek, M.1    Schmid, C.2
  • 13
    • 77953209947 scopus 로고    scopus 로고
    • Learning and using taxonomies for fast visual category recognition
    • G. Griffin and P. Perona. Learning and using taxonomies for fast visual category recognition. In CVPR, 2008.
    • (2008) CVPR
    • Griffin, G.1    Perona, P.2
  • 14
    • 0002346866 scopus 로고    scopus 로고
    • Hierarchically classifying documents using very few words
    • D. Koller and M. Sahami. Hierarchically classifying documents using very few words. In ICML, 1997.
    • (1997) ICML
    • Koller, D.1    Sahami, M.2
  • 15
    • 0002332781 scopus 로고    scopus 로고
    • Improving text classification by shrinkage in a hierarchy of classes
    • A. McCallum, R. Rosenfeld, T. Mitchell, and A. Ng. Improving text classification by shrinkage in a hierarchy of classes. In ICML, 1998.
    • (1998) ICML
    • McCallum, A.1    Rosenfeld, R.2    Mitchell, T.3    Ng, A.4
  • 16
    • 18744367558 scopus 로고    scopus 로고
    • Hierarchical document categorization with support vector machines
    • L. Cai and T. Hofmann. Hierarchical document categorization with support vector machines. In CIKM, 2004.
    • (2004) CIKM
    • Cai, L.1    Hofmann, T.2
  • 17
    • 70450172710 scopus 로고    scopus 로고
    • Learning to detect unseen object classes by between-class attribute transfer
    • C. Lampert, H. Nickisch, and S. Harmeling. Learning to detect unseen object classes by between-class attribute transfer. In CVPR, 2009.
    • (2009) CVPR
    • Lampert, C.1    Nickisch, H.2    Harmeling, S.3
  • 19
    • 34047200109 scopus 로고    scopus 로고
    • Sharing visual features for multiclass and multiview object detection
    • A. Torralba and K. Murphy. Sharing visual features for multiclass and multiview object detection. PAMI, 29(5), 2007.
    • (2007) PAMI , vol.29 , Issue.5
    • Torralba, A.1    Murphy, K.2
  • 21
    • 77953185204 scopus 로고    scopus 로고
    • Similarity functions for categorization: From monolithic to category specific
    • B. Babenko, S. Branson, and S. Belongie. Similarity functions for categorization: from monolithic to category specific. In ICCV, 2009.
    • (2009) ICCV
    • Babenko, B.1    Branson, S.2    Belongie, S.3
  • 22
    • 84864030708 scopus 로고    scopus 로고
    • Metric learning by collapsing classes
    • A. Globerson and S. Roweis. Metric learning by collapsing classes. In NIPS, pages 451-458. 2006.
    • (2006) NIPS , pp. 451-458
    • Globerson, A.1    Roweis, S.2
  • 24
    • 56449127513 scopus 로고    scopus 로고
    • Fast solvers and efficient implementations for distance metric learning
    • K. Weinberger and L. Saul. Fast solvers and efficient implementations for distance metric learning. In ICML, 2008.
    • (2008) ICML
    • Weinberger, K.1    Saul, L.2
  • 25
    • 78149488666 scopus 로고    scopus 로고
    • Hierarchical large margin nearest neighbor classification
    • Q. Chen and S. Sun. Hierarchical large margin nearest neighbor classification. In ICPR, 2010.
    • (2010) ICPR
    • Chen, Q.1    Sun, S.2
  • 26
    • 85162530133 scopus 로고    scopus 로고
    • Large margin multi-task metric learning
    • S. Parameswaran and K. Weinberger. Large margin multi-task metric learning. In NIPS, 2010.
    • (2010) NIPS
    • Parameswaran, S.1    Weinberger, K.2
  • 27
    • 79957815549 scopus 로고    scopus 로고
    • Sparse metric learning via smooth optimization
    • Y. Ying, K. Huang, and C. Campbell. Sparse metric learning via smooth optimization. In NIPS. 2009.
    • (2009) NIPS
    • Ying, Y.1    Huang, K.2    Campbell, C.3
  • 28
    • 80053457157 scopus 로고    scopus 로고
    • Hierarchical classification via orthogonal transfer
    • D. Zhou, L. Xiao, and M. Wu. Hierarchical classification via orthogonal transfer. In ICML, 2011.
    • (2011) ICML
    • Zhou, D.1    Xiao, L.2    Wu, M.3
  • 31
    • 50649123564 scopus 로고    scopus 로고
    • Exploiting object hierarchy: Combining models from different category levels
    • A. Zweig and D. Weinshall. Exploiting object hierarchy: Combining models from different category levels. In ICCV, 2007.
    • (2007) ICCV
    • Zweig, A.1    Weinshall, D.2
  • 32
    • 80052876786 scopus 로고    scopus 로고
    • What does classifying more than 10,000 image categories tell us?
    • J. Deng, A. Berg, K. Li, and L. Fei-Fei. What does classifying more than 10,000 image categories tell us? In ECCV, 2010.
    • (2010) ECCV
    • Deng, J.1    Berg, A.2    Li, K.3    Fei-Fei, L.4
  • 33
    • 80052913382 scopus 로고    scopus 로고
    • A discriminative latent model of object classes and attributes
    • Y. Wang and G. Mori. A discriminative latent model of object classes and attributes. In ECCV, 2010.
    • (2010) ECCV
    • Wang, Y.1    Mori, G.2
  • 34
    • 85194972808 scopus 로고
    • Regression shrinkage and selection via the lasso
    • R. Tibshirani. Regression shrinkage and selection via the lasso. J. Roy. Statistical Society, 58:267-288, 1994.
    • (1994) J. Roy. Statistical Society , vol.58 , pp. 267-288
    • Tibshirani, R.1
  • 36
    • 80052894360 scopus 로고    scopus 로고
    • Semantic label sharing for learning with many categories
    • R. Fergus, H. Bernal, Y.Weiss, and A. Torralba. Semantic label sharing for learning with many categories. In ECCV, 2010.
    • (2010) ECCV
    • Fergus, R.1    Bernal, H.2    Weiss, Y.3    Torralba, A.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.