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Volumn 4, Issue 2, 2013, Pages

Learning image-to-class distance metric for image classification

Author keywords

Distance metric learning; Image classification; Image to class distance; Nearest neighbor classification

Indexed keywords

CLASS IMBALANCE PROBLEMS; CONVEX OPTIMIZATION PROBLEMS; DISTANCE METRIC LEARNING; IMAGE-TO-CLASS DISTANCE; LARGE-SCALE DATASETS; NEAREST-NEIGHBOR CLASSIFICATIONS; OPTIMIZATION PROBLEMS; SUBGRADIENT DESCENT;

EID: 84876105426     PISSN: 21576904     EISSN: 21576912     Source Type: Journal    
DOI: 10.1145/2438653.2438659     Document Type: Review
Times cited : (9)

References (38)
  • 8
    • 84932617705 scopus 로고    scopus 로고
    • Learning generative visual models from few training examples: An Incremental bayesian approach tested on 101 object categories
    • FEI-FEI, L., FERGUS, R., AND PERONA, P. 2004. Learning generative visual models from few training examples: An Incremental bayesian approach tested on 101 object categories. In Proceedings of the CVPRWorkshop on Generative-Model Based Vision.
    • (2004) Proceedings of the CVPRWorkshop on Generative-Model Based Vision
    • Fei-Fei, L.1    Fergus, R.2    Perona, P.3
  • 10
    • 84864031890 scopus 로고    scopus 로고
    • Image retrieval and classification using local distance functions
    • FROME, A., SINGER, Y., AND MALIK, J. 2006. Image retrieval and classification using local distance functions. Adv. Neural Inf. Process. Syst. 19.
    • (2006) Adv. Neural Inf. Process. Syst. , vol.19
    • Frome, A.1    Singer, Y.2    Malik, J.3
  • 18
    • 77749342888 scopus 로고    scopus 로고
    • Face and human gait recognition using image-to-class distance
    • HUANG, Y., XU, D., AND CHAM, T.-J. 2010. Face and human gait recognition using image-to-class distance. IEEE Trans. Circuits Syst. Video Technol. 20, 3, 431-438.
    • (2010) IEEE Trans. Circuits Syst. Video Technol. , vol.20 , Issue.3 , pp. 431-438
    • Huang, Y.1    Xu, D.2    Cham, T.-J.3
  • 22
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • LOWE, D. G. 2004. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60, 2, 91-110.
    • (2004) Int. J. Comput. Vis. , vol.60 , Issue.2 , pp. 91-110
    • Lowe, D.G.1
  • 25
    • 0035328421 scopus 로고    scopus 로고
    • Modeling the shape of the scene: A holistic representation of the spatial envelope
    • OLIVA, A. AND TORRALBA, A. 2001. Modeling the shape of the scene: A holistic representation of the spatial envelope. Int. J. Comput. Vis. 42, 3, 145-175.
    • (2001) Int. J. Comput. Vis. , vol.42 , Issue.3 , pp. 145-175
    • Oliva, A.1    Torralba, A.2
  • 26
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • ROWEIS, S. AND SAUL, L. K. 2000. Nonlinear dimensionality reduction by locally linear embedding. Science 290, 5500, 2323-2326.
    • (2000) Science , vol.290 , Issue.5500 , pp. 2323-2326
    • Roweis, S.1    Saul, L.K.2
  • 27
    • 33746873280 scopus 로고    scopus 로고
    • Collaborative image retrieval via regularized metric learning
    • SI, L., JIN, R., HOI, S. C. H., AND LYU, M. R. 2006. Collaborative image retrieval via regularized metric learning. Multimedia Syst. 12, 1, 34-44.
    • (2006) Multimedia Syst , vol.12 , Issue.1 , pp. 34-44
    • Si, L.1    Jin, R.2    Hoi, S.C.H.3    Lyu, M.R.4
  • 28
    • 0034704229 scopus 로고    scopus 로고
    • A global geometric framework for nonlinear dimensionality reduction
    • TENENBAUM, J., DE SILVA, V., AND LANGFORD, J. C. 2000. A global geometric framework for nonlinear dimensionality reduction. Science 290, 5500, 2319-2323.
    • (2000) Science , vol.290 , Issue.5500 , pp. 2319-2323
    • Tenenbaum, J.1    De Silva, V.2    Langford, J.C.3
  • 33
    • 61749090884 scopus 로고    scopus 로고
    • Distance metric learning for large margin nearest neighbor classification
    • WEINBERGER, K. Q. AND SAUL, L. K. 2009. Distance metric learning for large margin nearest neighbor classification. J. Mach. Learn. Res. 10, 207-244.
    • (2009) J. Mach. Learn. Res. , vol.10 , pp. 207-244
    • Weinberger, K.Q.1    Saul, L.K.2
  • 34
    • 77953226691 scopus 로고    scopus 로고
    • Beyond the euclidean distance: Creating effective visual codebooks using the histogram intersection kernel
    • WU, J. AND REHG, J. M. 2009. Beyond the euclidean distance: Creating effective visual codebooks using the histogram intersection kernel. In Proceedings of the IEEE International Conference on Computer Vision.
    • (2009) Proceedings of the IEEE International Conference on Computer Vision
    • Wu, J.1    Rehg, J.M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.