Support Vector Machines for Mathematical Symbol Recognition
Identifieur interne : 001005 ( Main/Exploration ); précédent : 001004; suivant : 001006Support Vector Machines for Mathematical Symbol Recognition
Auteurs : Christopher Malon [Japon] ; Seiichi Uchida [Japon] ; Masakazu Suzuki (mathématicien) [Japon]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2006.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
Abstract: 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.
Url:
DOI: 10.1007/11815921_14
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">Abstract: 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.</div>
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