메뉴 건너뛰기




Volumn 1, Issue , 2006, Pages 330-335

Learning boosted asymmetric classifiers for object detection

Author keywords

[No Author keywords available]

Indexed keywords

ASYMMETRIC ADABOOST ALGORITHMS; FALSE ACCEPT RATE (FAR); FALSE REJECT RATE (FRR);

EID: 33845597493     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2006.166     Document Type: Conference Paper
Times cited : (26)

References (23)
  • 1
    • 0038391397 scopus 로고    scopus 로고
    • How to use Boosting for tumor classification with gene expression data
    • M. Dettling and P. Bühlmann. How to use Boosting for tumor classification with gene expression data. Bioinformatics, 19:1061-1069, 2003.
    • (2003) Bioinformatics , vol.19 , pp. 1061-1069
    • Dettling, M.1    Bühlmann, P.2
  • 5
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to Boosting
    • Y. Freund and R. E. Schapire. A decision-theoretic generalization of on-line learning and an application to Boosting. International Journal of Computer and System Sciences, 5:119-139, 1997.
    • (1997) International Journal of Computer and System Sciences , vol.5 , pp. 119-139
    • Freund, Y.1    Schapire, R.E.2
  • 6
    • 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. Annals of Statistics, 28:337-407, 2000.
    • (2000) Annals of Statistics , vol.28 , pp. 337-407
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 9
    • 0028324717 scopus 로고
    • Cryptographic limitations on learning Boolean formulae and finite automata
    • M. Kearns and L. O. Valiant. Cryptographic limitations on learning Boolean formulae and finite automata. Journal of the ACM, 41:67-95, 1994.
    • (1994) Journal of the ACM , vol.41 , pp. 67-95
    • Kearns, M.1    Valiant, L.O.2
  • 11
    • 33845579381 scopus 로고    scopus 로고
    • Robust real-time face detection based on cost-sensitive AdaBoost
    • Y. Ma and X. Q. Ding. Robust real-time face detection based on cost-sensitive AdaBoost, method, pages 465-478, 2003.
    • (2003) Method , pp. 465-478
    • Ma, Y.1    Ding, X.Q.2
  • 13
    • 35248862907 scopus 로고    scopus 로고
    • An introduction to Boosting and Leveraging
    • Springer-Verlag
    • R. Meir and G. Ratsch. An introduction to Boosting and Leveraging. In Advanced Lectures on Maching Learning, volume LNAI 2600, pages 118-183. Springer-Verlag, 2003.
    • (2003) Advanced Lectures on Maching Learning , vol.LNAI 2600 , pp. 118-183
    • Meir, R.1    Ratsch, G.2
  • 18
    • 0025448521 scopus 로고
    • The strength of weak learnability
    • R. E. Schapire. The strength of weak learnability. Machine Learning, 5:197-227, 1990.
    • (1990) Machine Learning , vol.5 , pp. 197-227
    • Schapire, R.E.1
  • 19
    • 0033281701 scopus 로고    scopus 로고
    • Improved Boosting algorithms using confidence-rated predictions
    • R. E. Schapire and Y. Singer. Improved Boosting algorithms using confidence-rated predictions. Machine Learning, 37:297-336, 1999.
    • (1999) Machine Learning , vol.37 , pp. 297-336
    • Schapire, R.E.1    Singer, Y.2
  • 20
    • 0034243471 scopus 로고    scopus 로고
    • Boosting neural networks
    • H. Schwenk and Y. Bengio. Boosting neural networks. Neural Computation, 12:1869-1887, 2000.
    • (2000) Neural Computation , vol.12 , pp. 1869-1887
    • Schwenk, H.1    Bengio, Y.2
  • 22
    • 2442516613 scopus 로고    scopus 로고
    • Fast and robust classification using asymmetric Adaboost and a detector cascade
    • P. Viola and M. Jones. Fast and robust classification using asymmetric Adaboost and a detector cascade. Neural Information Processing Systems, pages 1311-1318, 2001.
    • (2001) Neural Information Processing Systems , pp. 1311-1318
    • Viola, P.1    Jones, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.