Presentation | 2006-02-23 Support Vector Machines for Mathematical Symbol Recognition Christopher MALON, Masakazu SUZUKI, Seiichi UCHIDA, |
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Abstract(in Japanese) | (See Japanese page) |
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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Committee | PRMU |
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Conference Date | 2006/2/16(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Pattern Recognition and Media Understanding (PRMU) |
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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 |
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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 |
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