A dynamical learning method with SVM and its application on bank slip recognition

CHEN Zengzhao; YANG Yang; DONG Cailin; HE Xiuling

doi:10.13374/j.issn1001-053x.2006.02.045

Volume 28 Issue 2

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CHEN Zengzhao, YANG Yang, DONG Cailin, HE Xiuling. A dynamical learning method with SVM and its application on bank slip recognition[J]. Chinese Journal of Engineering, 2006, 28(2): 199-202. doi: 10.13374/j.issn1001-053x.2006.02.045

Citation:

CHEN Zengzhao, YANG Yang, DONG Cailin, HE Xiuling. A dynamical learning method with SVM and its application on bank slip recognition[J]. Chinese Journal of Engineering, 2006, 28(2): 199-202. doi: 10.13374/j.issn1001-053x.2006.02.045

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A dynamical learning method with SVM and its application on bank slip recognition

doi: 10.13374/j.issn1001-053x.2006.02.045

1. Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China;
2. The Center for Optimal Control & Discrete Mathematics, Central China Normal University, Wuhan 430079, China

Received Date: 2004-12-26
Rev Recd Date: 2005-06-06

Available Online: 2021-08-24

Abstract

Abstract

This paper introduces a dynamical learning method using support vector machine (SVM). This method can solve such machine learning problems as the difficulties in gathering training samples and the change of samples with outer environment. It is proved that SVM classifiers can achieve optimal performance after using this method in tracking the change of samples. A bank slip OCR system designed by this method proves the validity.
- support vector machine,
- dynamical learning,
- machine learning,
- handwritten character recognition,
- bank slip recognition