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» Combining SVM Classifiers for Handwritten Digit Recognition
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ICPR
2010
IEEE
13 years 11 months ago
Evolving Fuzzy Classifiers: Application to Incremental Learning of Handwritten Gesture Recognition Systems
In this paper, we present a new method to design customizable self-evolving fuzzy rule-based classifiers. The presented approach combines an incremental clustering algorithm with a...
Abdullah Almaksour, Eric Anquetil, Solen Quiniou, ...
ICPR
2004
IEEE
14 years 8 months ago
Applying A Hybrid Method To Handwritten Character Recognition
In this paper, we propose a new prototype learning/matching method that can be combined with support vector machines (SVM) in pattern recognition. This hybrid method has the follo...
Chin-Chin Lin, Chun-Jen Chen, Fu Chang
ICFHR
2010
140views Biometrics» more  ICFHR 2010»
13 years 2 months ago
Part-Based Recognition of Handwritten Characters
In the part-based recognition method proposed in this paper, a handwritten character image is represented by just a set of local parts. Then, each local part of the input pattern ...
Seiichi Uchida, Marcus Liwicki
ICDAR
2011
IEEE
12 years 7 months ago
Objective Function Design for MCE-Based Combination of On-line and Off-line Character Recognizers for On-line Handwritten Japane
—This paper describes effective object function design for combining on-line and off-line character recognizers for on-line handwritten Japanese text recognition. We combine on-l...
Bilan Zhu, Jinfeng Gao, Masaki Nakagawa
DAS
2006
Springer
13 years 11 months ago
Combining Multiple Classifiers for Faster Optical Character Recognition
Traditional approaches to combining classifiers attempt to improve classification accuracy at the cost of increased processing. They may be viewed as providing an accuracy-speed tr...
Kumar Chellapilla, Michael Shilman, Patrice Simard