Handprinted Hiragana Recognition Using Support Vector Machines

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Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)

Ontario, Canada

August 06-August 08

ISBN: 0-7695-1692-0

	ASCII Text	x
	Ken-ichi Maruyama, Minoru Maruyama, Hidetoshi Miyao, Yasuaki Nakano, "Handprinted Hiragana Recognition Using Support Vector Machines," Frontiers in Handwriting Recognition, International Workshop on, pp. 55, Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02), 2002.

	BibTex	x
	@article{ 10.1109/IWFHR.2002.1030884, author = {Ken-ichi Maruyama and Minoru Maruyama and Hidetoshi Miyao and Yasuaki Nakano}, title = {Handprinted Hiragana Recognition Using Support Vector Machines}, journal ={Frontiers in Handwriting Recognition, International Workshop on}, volume = {0}, year = {2002}, isbn = {0-7695-1692-0}, pages = {55}, doi = {http://doi.ieeecomputersociety.org/10.1109/IWFHR.2002.1030884}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Frontiers in Handwriting Recognition, International Workshop on TI - Handprinted Hiragana Recognition Using Support Vector Machines SN - 0-7695-1692-0 SP EP A1 - Ken-ichi Maruyama, A1 - Minoru Maruyama, A1 - Hidetoshi Miyao, A1 - Yasuaki Nakano, PY - 2002 KW - null VL - 0 JA - Frontiers in Handwriting Recognition, International Workshop on ER -

Ken-ichi Maruyama, Shinshu University

Minoru Maruyama, Shinshu University

Hidetoshi Miyao, Shinshu University

Yasuaki Nakano, Shinshu University

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IWFHR.2002.1030884

This paper describes a method to improve the cumulative recognition rates of pattern recognition using Decision Directed Acyclic Graph (DDAG) based on support vector machines (SVM). Though the original DDAG has high level of performance and its execution speed is fast, it does not consider the so-called cumulative recognition rate. We construct DDAG which can incorporate the cumulative recognition rate. As a result of our experiment for the hand-printed Hiragana characters in JEITA-HP, the cumulative recognition rate is improved and its execution time is almost the same as the original DDAG and 30 times faster than Max Win Algorithm which is one of famous recognition methods using support vector machines for a multi-class problem.

Citation:

Ken-ichi Maruyama, Minoru Maruyama, Hidetoshi Miyao, Yasuaki Nakano, "Handprinted Hiragana Recognition Using Support Vector Machines," iwfhr, pp.55, Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02), 2002

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