Presentation 2006-02-23
Support Vector Machines for Mathematical Symbol Recognition
Christopher MALON, Masakazu SUZUKI, Seiichi UCHIDA,
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Abstract(in English) Mathematical formulas challenge an OCR system with a range of similar-looking characters whose bold, calligraphic, and italic varieties must be recognized distinctly, though the fonts to be used in an article are not known in advance. We describe the use of support vector machines (SVM) to learn and predict about 300 classes of styled characters and symbols.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) mathematical formula recognition / symbol recognition / character recognition / support vector machines
Paper # TL2005-57,PRMU2005-192
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Conference Information
Committee PRMU
Conference Date 2006/2/16(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Support Vector Machines for Mathematical Symbol Recognition
Sub Title (in English)
Keyword(1) mathematical formula recognition
Keyword(2) symbol recognition
Keyword(3) character recognition
Keyword(4) support vector machines
1st Author's Name Christopher MALON
1st Author's Affiliation MIT Department of Mathematics()
2nd Author's Name Masakazu SUZUKI
2nd Author's Affiliation Engineering Division, Faculty of Mathematics, Kyushu University
3rd Author's Name Seiichi UCHIDA
3rd Author's Affiliation Faculty of Information Science and Electrical Engineering, Kyushu University
Date 2006-02-23
Paper # TL2005-57,PRMU2005-192
Volume (vol) vol.105
Number (no) 614
Page pp.pp.-
#Pages 6
Date of Issue