کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9699587 | 1461748 | 2005 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Off-line cursive handwriting recognition using multiple classifier systems-on the influence of vocabulary, ensemble, and training set size
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی برق و الکترونیک
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چکیده انگلیسی
Unconstrained handwritten text recognition is one of the most difficult problems in the field of pattern recognition. Recently, a number of classifier creation and combination methods, known as ensemble methods, have been proposed in the field of machine learning. They have shown improved recognition performance over single classifiers. In this paper, we examine the influence of the vocabulary size, the number of training samples, and the number of classifiers on the performance of three ensemble methods in the context of cursive handwriting recognition. All experiments were conducted using an off-line handwritten word recognizer based on hidden Markov models (HMMs).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Optics and Lasers in Engineering - Volume 43, Issues 3â5, MarchâMay 2005, Pages 437-454
Journal: Optics and Lasers in Engineering - Volume 43, Issues 3â5, MarchâMay 2005, Pages 437-454
نویسندگان
Simon Günter, Horst Bunke,