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Volumn , Issue , 2011, Pages 1007-1011

Perceptron learning of modified quadratic discriminant function

Author keywords

active set; Chinese handwritten character recognition; dynamic margin; MQDF; Perceptron

Indexed keywords

ACTIVE SETS; CHINESE HANDWRITTEN CHARACTER; DYNAMIC MARGIN; MQDF; PERCEPTRON;

EID: 82355182302     PISSN: 15205363     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDAR.2011.204     Document Type: Conference Paper
Times cited : (12)

References (12)
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  • 3
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    • Y. Wang, Q. Huo. Sample-separation-margin based minimum classification error training of pattern classifiers with quadratic discriminant functions. ICASSP, 2010.
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    • Wang, Y.1    Huo, Q.2
  • 5
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    • Minimum classification error rate methods for speech recognition
    • PII S1063667697035937
    • B.-H. Juang, W. Chou, C.-H. Lee. Minimum classification error rate methods for speech recognition. IEEE Trans. Speech and Audio Processing, 5(3): 257-265, 1997. (Pubitemid 127745998)
    • (1997) IEEE Transactions on Speech and Audio Processing , vol.5 , Issue.3 , pp. 257-265
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  • 6
    • 11144273669 scopus 로고
    • The perceptron: A probabilistic model for information storage and organization in the brain
    • F. Rosenblatt. The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review, 65 (6):386-408, 1958.
    • (1958) Psychological Review , vol.65 , Issue.6 , pp. 386-408
    • Rosenblatt, F.1
  • 7
    • 70450183825 scopus 로고    scopus 로고
    • A fast online algorithm for large margin training of continuous density hidden markov models
    • C. Cheng, F. Sha, L. Saul. A fast online algorithm for large margin training of continuous density hidden markov models. Proceedings of Interspeech, 2009.
    • Proceedings of Interspeech, 2009
    • Cheng, C.1    Sha, F.2    Saul, L.3
  • 9
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    • Regularized margin-based conditional log-likelihood loss for prototype learning
    • X.-B. Jin, C.-L. Liu, X.-W. Hou. Regularized margin-based conditional log-likelihood loss for prototype learning. Pattern Recognition, 43: 2428-2438, 2010.
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    • Jin, X.-B.1    Liu, C.-L.2    Hou, X.-W.3
  • 11
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    • Handwritten digit recognition: Benchmarking of state-of-the-art techniques
    • DOI 10.1016/S0031-3203(03)00085-2
    • C.-L. Liu, K. Nakashima, H. Sako, H. Fujisawa. Handwritten digit recognition: benchmarking of state-of-the-art techniques. Pattern Recognition, 36: 2271-2285, 2003. (Pubitemid 36953768)
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    • Online and offline handwritten Chinese character recognition: Benchmarking on new databases
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.