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Volumn 3, Issue , 2012, Pages 1718-1726

Semantic kernel forests from multiple taxonomies

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY IMPROVEMENT; DISCRIMINATIVE FEATURES; HIERARCHICAL TAXONOMY; OBJECT CATEGORIES; REGULARIZATION TERMS; SEMANTIC RELATIONSHIPS; VISUAL CLASSIFICATION; VISUAL RECOGNITION;

EID: 84877777363     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (31)

References (37)
  • 1
    • 33645146449 scopus 로고    scopus 로고
    • Histograms of oriented gradients for human detection
    • N. Dalal and B. Triggs. Histograms of Oriented Gradients for Human Detection. In CVPR, 2005.
    • (2005) CVPR
    • Dalal, N.1    Triggs, B.2
  • 2
    • 77955996870 scopus 로고    scopus 로고
    • Locality-constrained linear coding for image classification
    • J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong. Locality-Constrained Linear Coding for Image Classification. In CVPR, 2010.
    • (2010) CVPR
    • Wang, J.1    Yang, J.2    Yu, K.3    Lv, F.4    Huang, T.5    Gong, Y.6
  • 4
    • 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
  • 5
    • 34948830130 scopus 로고    scopus 로고
    • Semantic hierarchies for visual object recognition
    • M. Marszalek and C. Schmid. Semantic hierarchies for visual object recognition. In CVPR, 2007.
    • (2007) CVPR
    • Marszalek, M.1    Schmid, C.2
  • 6
    • 54749092170 scopus 로고    scopus 로고
    • 80 million tiny images: A large dataset for non-parametric object and scene recognition
    • A. Torralba, R. Fergus, and W. T. Freeman. 80 million Tiny Images: a Large Dataset for Non-Parametric Object and Scene Recognition. PAMI, 30(11):1958-1970, 2008.
    • (2008) PAMI , vol.30 , Issue.11 , pp. 1958-1970
    • Torralba, A.1    Fergus, R.2    Freeman, W.T.3
  • 8
    • 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
  • 9
    • 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
  • 10
    • 85162445667 scopus 로고    scopus 로고
    • Learning a tree of metrics with disjoint visual features
    • S. J. Hwang, K. Grauman, and F. Sha. Learning a tree of metrics with disjoint visual features. In NIPS, 2011.
    • (2011) NIPS
    • Hwang, S.J.1    Grauman, K.2    Sha, F.3
  • 12
    • 85162050606 scopus 로고    scopus 로고
    • Label embedding trees for large multi-class task
    • S. Bengio, J. Weston, and D. Grangier. Label Embedding Trees for Large Multi-Class Task. In NIPS, 2010.
    • (2010) NIPS
    • Bengio, S.1    Weston, J.2    Grangier, D.3
  • 13
    • 85162353669 scopus 로고    scopus 로고
    • Fast and balanced: Efficient label tree learning for large scale object recognition
    • J. Deng, S. Satheesh, A. Berg, and L. Fei Fei. Fast and balanced: Efficient label tree learning for large scale object recognition. In NIPS, 2011.
    • (2011) NIPS
    • Deng, J.1    Satheesh, S.2    Berg, A.3    Fei Fei, L.4
  • 14
    • 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
  • 15
    • 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
  • 16
    • 51949092342 scopus 로고    scopus 로고
    • Learning and using taxonomies for fast visual categorization
    • G. Griffin and P. Perona. Learning and using taxonomies for fast visual categorization. In CVPR, 2008.
    • (2008) CVPR
    • Griffin, G.1    Perona, P.2
  • 17
    • 84856654322 scopus 로고    scopus 로고
    • Discriminative learning of relaxed hierarchy for large-scale visual recognition
    • T. Gao and D. Koller. Discriminative learning of relaxed hierarchy for large-scale visual recognition. In ICCV, 2011.
    • (2011) ICCV
    • Gao, T.1    Koller, D.2
  • 20
    • 77955991925 scopus 로고    scopus 로고
    • Building and using a semantivisual image hierarchy
    • L.-J. Li, C. Wang, Y. Lim, D. Blei, and L. Fei-Fei. Building and using a semantivisual image hierarchy. In CVPR, 2010.
    • (2010) CVPR
    • Li, L.-J.1    Wang, C.2    Lim, Y.3    Blei, D.4    Fei-Fei, L.5
  • 21
    • 77956548668 scopus 로고    scopus 로고
    • Tree-guided group lasso for multi-task regression with structured sparsity
    • S. Kim and E. Xing. Tree-guided group lasso for multi-task regression with structured sparsity. In ICML, 2010.
    • (2010) ICML
    • Kim, S.1    Xing, E.2
  • 22
    • 10044285992 scopus 로고    scopus 로고
    • Canonical correlation analysis: An overview with application to learning methods
    • D. R. Hardoon, S. Szedmak, and J. Shawe-Taylor. Canonical Correlation Analysis: An Overview with Application to Learning Methods. Neural Computation, 16(12), 2004.
    • (2004) Neural Computation , vol.16 , Issue.12
    • Hardoon, D.R.1    Szedmak, S.2    Shawe-Taylor, J.3
  • 25
    • 2942723846 scopus 로고    scopus 로고
    • A divisive information-theoretic feature clustering algorithm for text classification
    • I. Dhillon, S. Mallela, and R. Kumar. A divisive information-theoretic feature clustering algorithm for text classification. Journal of Machine Learning Research, 3:1265-1287, 2003.
    • (2003) Journal of Machine Learning Research , vol.3 , pp. 1265-1287
    • Dhillon, I.1    Mallela, S.2    Kumar, R.3
  • 28
    • 77953196304 scopus 로고    scopus 로고
    • Scene discovery by matrix factorization
    • N. Loeff and A. Farhadi. Scene Discovery by Matrix Factorization. In ECCV, 2008.
    • (2008) ECCV
    • Loeff, N.1    Farhadi, A.2
  • 29
    • 80052908079 scopus 로고    scopus 로고
    • Sharing features between objects and their attributes
    • S. J. Hwang, F. Sha, and K. Grauman. Sharing features between objects and their attributes. In CVPR, 2011.
    • (2011) CVPR
    • Hwang, S.J.1    Sha, F.2    Grauman, K.3
  • 30
    • 14344252374 scopus 로고    scopus 로고
    • Multiple kernel learning, conic duality, and the SMO algorithm
    • F. Bach, G. Lanckriet, and M. Jordan. Multiple Kernel Learning, Conic Duality, and the SMO Algorithm. In ICML, 2004.
    • (2004) ICML
    • Bach, F.1    Lanckriet, G.2    Jordan, M.3
  • 31
    • 50649115912 scopus 로고    scopus 로고
    • Learning the discriminative power-invariance trade-off
    • M. Varma and D. Ray. Learning the discriminative power-invariance trade-off. In ICCV, 2007.
    • (2007) ICCV
    • Varma, M.1    Ray, D.2
  • 32
    • 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
  • 33
    • 33749550361 scopus 로고    scopus 로고
    • Distance metric learning for large margin nearest neighbor classification
    • K. Weinberger, J. Blitzer, and L. Saul. Distance Metric Learning for Large Margin Nearest Neighbor Classification. In NIPS, 2006.
    • (2006) NIPS
    • Weinberger, K.1    Blitzer, J.2    Saul, L.3
  • 34
    • 85027388762 scopus 로고    scopus 로고
    • Exploring large feature spaces with hierarchical multiple kernel learning
    • F. Bach. Exploring large feature spaces with hierarchical multiple kernel learning. In NIPS, 2008.
    • (2008) NIPS
    • Bach, F.1
  • 37
    • 84856200679 scopus 로고    scopus 로고
    • Attribute learning in large-scale datasets
    • O. Russakovsky and L. Fei-Fei. Attribute learning in large-scale datasets. In ECCV, 2010. 17926
    • (2010) ECCV , pp. 17926
    • Russakovsky, O.1    Fei-Fei, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.