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Volumn I, Issue , 2005, Pages 494-501

Pruning training sets for learning of object categories

Author keywords

[No Author keywords available]

Indexed keywords

DATA ACQUISITION; LEARNING SYSTEMS; MATHEMATICAL MODELS; PROBLEM SOLVING; ROBUSTNESS (CONTROL SYSTEMS);

EID: 24644505329     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2005.283     Document Type: Conference Paper
Times cited : (154)

References (21)
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    • Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography
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    • Fischler, M.1    Bolles, R.2
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    • [http://www.google.com]
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    • Koistinen, P.1
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    • Constructing heterogeneous committees using input feature grouping: Application to economic forecasting
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    • Liao, Y.1    Moody, J.2
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    • Magdon-Ismail. M., No Free Lunch for Noise Prediction, Neural Computation, 12:547-564, 2000.
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    • Using the forest to see the trees: A graphical model relating features objects and scenes
    • Murphy, K., Torralba, A., Freeman, B., Using the forest to see the trees: a graphical model relating features objects and scenes. Advances in NIPS, 2003
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    • Murphy, K.1    Torralba, A.2    Freeman, B.3
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    • Generalization Error Estimates and Training Data Valuation, Ph.D. Thesis, California Institute of Technology
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.