Presentation 1998/6/19
Dictionary learning by adding hyperspherical templates
Yoshimasa KIMURA, Toru WAKAHARA, Toshiaki SUGIMURA,
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Abstract(in English) The traditional adding template method has a serious flaw in that the recognition rate of learnt patterns decreases as dictionary learning progresses. To solve this problem, we present a hierarchical system that outputs the recognition result from Voronoi regions given by reference templates as the first candidate. Next, hyperspherical classifiers given by the addition of templates generated in the Voronoi region determine the correct candidate. The hierarchical system promotes the recognition rate by dictionary learning and succeeds in overcoming the problem in experiments on handwritten Kanji pattern recognition.
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Keyword(in English) Dictionary learning / hyperspherical templates / hierarchical classification / handwritten Kanji character recognition
Paper # PRMU98-37
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Conference Information
Committee PRMU
Conference Date 1998/6/19(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Dictionary learning by adding hyperspherical templates
Sub Title (in English)
Keyword(1) Dictionary learning
Keyword(2) hyperspherical templates
Keyword(3) hierarchical classification
Keyword(4) handwritten Kanji character recognition
1st Author's Name Yoshimasa KIMURA
1st Author's Affiliation NTT Human Interface Laboratories()
2nd Author's Name Toru WAKAHARA
2nd Author's Affiliation NTT Human Interface Laboratories
3rd Author's Name Toshiaki SUGIMURA
3rd Author's Affiliation NTT Human Interface Laboratories
Date 1998/6/19
Paper # PRMU98-37
Volume (vol) vol.98
Number (no) 127
Page pp.pp.-
#Pages 8
Date of Issue