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Volumn 7, Issue 1, 2007, Pages 71-88

Word segmentation of handwritten text using supervised classification techniques

Author keywords

Handwriting; McNemar's test; Mutual information; Supervised classification

Indexed keywords

ALGORITHMS; DATA REDUCTION; EDUCATION COMPUTING; FEATURE EXTRACTION; INFORMATION ANALYSIS; LEARNING SYSTEMS;

EID: 33750957103     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2004.10.009     Document Type: Article
Times cited : (15)

References (17)
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    • T. Butler, Human Interaction with Digital Ink: Legibility Measurement and Structural Analysis, Ph.D. Thesis, Department of Computer Science, University of Hertfordshire, Hertfordshire, UK.
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    • Feature extraction by non-parametric mutual information maximization
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    • Maximum likelihood from incomplete data via the EM algorithm
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    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
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    • Approximate statistical tests for comparing supervised classification learning algorithms
    • Dietterich T.G. Approximate statistical tests for comparing supervised classification learning algorithms. Neural Comput. 10 7 (1998) 895-1923
    • (1998) Neural Comput. , vol.10 , Issue.7 , pp. 895-1923
    • Dietterich, T.G.1
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    • Specifying gestures by example
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.