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Volumn , Issue , 2009, Pages 911-918

An instance selection approach to multiple instance learning

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS; LEARNING SYSTEMS;

EID: 70450284668     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2009.5206655     Document Type: Conference Paper
Times cited : (25)

References (18)
  • 1
    • 70450228408 scopus 로고    scopus 로고
    • Mosek. http://www.mosek.com, 2001.
    • (2001) Mosek
  • 6
    • 84863161940 scopus 로고    scopus 로고
    • Image categorization by learning and reasoning with regions
    • Y. Chen and J. Z. Wang. Image categorization by learning and reasoning with regions. Journal of Machine Learning Research, 5(913-939), 2004.
    • (2004) Journal of Machine Learning Research , vol.5 , Issue.913-939
    • Chen, Y.1    Wang, J.Z.2
  • 7
    • 0010442827 scopus 로고    scopus 로고
    • On the algorithmic implementation of multiclass kernel-based vector machines
    • K. Crammer and Y. Singer. On the algorithmic implementation of multiclass kernel-based vector machines. Journal of Machine Learning Research, 2:265-292, 2001.
    • (2001) Journal of Machine Learning Research , vol.2 , pp. 265-292
    • Crammer, K.1    Singer, Y.2
  • 9
    • 0030649484 scopus 로고    scopus 로고
    • Solving the multiple-instance problem with axis-parallel rectangles
    • T. Dietterich, R. Lathrop, and T. Lozano-Perez. Solving the multiple-instance problem with axis-parallel rectangles. Artificial Intelligence, 89(1-2):31 - 71, 1997.
    • (1997) Artificial Intelligence , vol.89 , Issue.1-2 , pp. 31-71
    • Dietterich, T.1    Lathrop, R.2    Lozano-Perez, T.3
  • 11
    • 84932617705 scopus 로고    scopus 로고
    • Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories
    • L. Fei-Fei, R. Fergus, and P. Perona. Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories. In CVPR Workshop on Generative-Model Based Vision, 2004.
    • (2004) CVPR Workshop on Generative-Model Based Vision
    • Fei-Fei, L.1    Fergus, R.2    Perona, P.3
  • 12
    • 34247576789 scopus 로고    scopus 로고
    • The pyramid match kernel: Efficient learning with sets of features
    • K. Grauman and T. Darrell. The pyramid match kernel: Efficient learning with sets of features. Journal of Machine Learning Research, 8:725-760, 2007. (Pubitemid 46677049)
    • (2007) Journal of Machine Learning Research , vol.8 , pp. 725-760
    • Grauman, K.1    Darrell, T.2
  • 14
    • 33845572523 scopus 로고    scopus 로고
    • Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories
    • S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In Computer Vision and Pattern Recognition, 2006.
    • (2006) Computer Vision and Pattern Recognition
    • Lazebnik, S.1    Schmid, C.2    Ponce, J.3
  • 15
    • 84898935332 scopus 로고    scopus 로고
    • A framework for multipleinstance learning
    • O. Maron and T. Lozano-Perez. A framework for multipleinstance learning. In NIPS, 1998.
    • (1998) NIPS
    • Maron, O.1    Lozano-Perez, T.2
  • 16
    • 38349018853 scopus 로고    scopus 로고
    • Evaluating multi-class multiple-instance learning for image categorization
    • X. Xu and B. Li. Evaluating multi-class multiple-instance learning for image categorization. In Asian Conf. on Computer Vision, pages 155-165, 2007.
    • (2007) Asian Conf. on Computer Vision , pp. 155-165
    • Xu, X.1    Li, B.2
  • 17
    • 0344551865 scopus 로고    scopus 로고
    • Improved fast gauss transform and efficient kernel density estimation
    • C. Yang, R. Duraiswami, and L. Davis. Improved fast gauss transform and efficient kernel density estimation. In Intl. Conf. Computer Vision, pages 464-471, 2003.
    • (2003) Intl. Conf. Computer Vision , pp. 464-471
    • Yang, C.1    Duraiswami, R.2    Davis, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.