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Volumn , Issue , 2012, Pages 2706-2710

Multiple instance real boosting with aggregation functions

Author keywords

[No Author keywords available]

Indexed keywords

AGGREGATION FUNCTIONS; MILBOOST; MULTIPLE INSTANCES; MULTIPLE-INSTANCE LEARNING; ORDERED WEIGHTED AVERAGING;

EID: 84874562882     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (8)

References (16)
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    • Andrews, S.1    Tsochantaridis, I.2    Hofmann, T.3
  • 2
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    • Visual tracking with online multiple instance learning
    • B. Babenko, M. Yang, and S. Belongie. Visual tracking with online multiple instance learning. In CVPR, 2009.
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    • Babenko, B.1    Yang, M.2    Belongie, S.3
  • 4
    • 33947180489 scopus 로고    scopus 로고
    • Miles: Multiple-instance learning via embedded instance selection
    • Y. Chen, J. Bi, and J. Wang. Miles: Multiple-instance learning via embedded instance selection. T-PAMI, 28(12):1931-1947, 2006.
    • (2006) T-PAMI , vol.28 , Issue.12 , pp. 1931-1947
    • Chen, Y.1    Bi, J.2    Wang, J.3
  • 5
    • 0030649484 scopus 로고    scopus 로고
    • Solving the multiple instance problem with axis-parallel rectangles
    • T. Dietterich, R. Lathrop, and T. Lozano-Pérez. 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-Pérez, T.3
  • 7
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression: A statistical view of boosting
    • J. Friedman, T. Hastie, and R. Tibshirani. Additive logistic regression: A statistical view of boosting. The annals of statistics, 28(2):337-407, 2000.
    • (2000) The Annals of Statistics , vol.28 , Issue.2 , pp. 337-407
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 8
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    • Deterministic annealing for multiple-instance learning
    • P. Gehler and O. Chapelle. Deterministic annealing for multiple-instance learning. In AISTATS, 2007.
    • (2007) AISTATS
    • Gehler, P.1    Chapelle, O.2
  • 9
    • 84864323247 scopus 로고    scopus 로고
    • Miforests: Multiple-instance learning with randomized trees
    • C. Leistner, A. Saffari, and H. Bischof. Miforests: Multiple-instance learning with randomized trees. In ECCV, 2010.
    • (2010) ECCV
    • Leistner, C.1    Saffari, A.2    Bischof, H.3
  • 11
    • 33750948815 scopus 로고    scopus 로고
    • Ordered weighted averaging with fuzzy quantifiers: Gis-based multicriteria evaluation for landuse suitability analysis
    • J. Malczewski. Ordered weighted averaging with fuzzy quantifiers: Gis-based multicriteria evaluation for landuse suitability analysis. Int. Jour. of Applied Earth Observation and Geoinformation, 8(4):270-277, 2006.
    • (2006) Int. Jour. of Applied Earth Observation and Geoinformation , vol.8 , Issue.4 , pp. 270-277
    • Malczewski, J.1
  • 12
    • 0000034034 scopus 로고    scopus 로고
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  • 13
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    • Multiple instance boosting for object detection
    • P. Viola, J. Platt, and C. Zhang. Multiple instance boosting for object detection. In NIPS, 2006.
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    • Viola, P.1    Platt, J.2    Zhang, C.3
  • 14
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    • On ordered weighted averaging aggregation operators in multicriteria decision making
    • R. Yager. On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Trans. Systems, Man and Cybernetics, 18(1):183-190, 1988.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.