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Volumn 3733 LNCS, Issue , 2005, Pages 575-584

Boosting classifiers for music genre classification

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER MUSIC; FEATURE EXTRACTION; INFORMATION RETRIEVAL SYSTEMS; MATHEMATICAL MODELS; PROBLEM SOLVING;

EID: 33646511069     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Conference Paper
Times cited : (8)

References (12)
  • 5
    • 0010020774 scopus 로고    scopus 로고
    • Scanning the dial: An exploration of factors in identification of musical style
    • Perrot, D., Gjerdigen, R.: Scanning the dial: An exploration of factors in identification of musical style. In: Proc. Soc. Music Perception Cognition. (1999) 88
    • (1999) Proc. Soc. Music Perception Cognition , pp. 88
    • Perrot, D.1    Gjerdigen, R.2
  • 9
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • Freund, Y., Schapire, R.E.: A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences 55 (1997) 119-139
    • (1997) Journal of Computer and System Sciences , vol.55 , pp. 119-139
    • Freund, Y.1    Schapire, R.E.2
  • 10
    • 0021404166 scopus 로고
    • Mixture densities, maximum likelihood and the em algorithm
    • Redner, R.A., Walker, H.F.: Mixture densities, maximum likelihood and the EM algorithm. SIAM Rev. 26 (1984) 195-239
    • (1984) SIAM Rev. , vol.26 , pp. 195-239
    • Redner, R.A.1    Walker, H.F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.