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2013 12th International Conference on Document Analysis and Recognition (2007)
Curitiba, Parana, Brazil
Sept. 23, 2007 to Sept. 26, 2007
ISSN: 1520-5363
ISBN: 0-7695-2822-8
pp: 859-863
S. Watt , University of Western Ontario
B. Keshari , University of Western Ontario
ABSTRACT
Recognition of mathematical symbols is a challenging task, with a large set with many similar symbols. We present a support vector machine based hybrid recognition system that uses both online and offline information for classifica- tion. Probabilistic outputs from the two support vector ma- chine based multi-class classifiers running in parallel are combined by taking a weighted sum. Results from the exper- iments show that giving slightly higher weight to the on-line information produces better results. The overall error rate of the hybrid system is lower than that of both the online and offline recognition systems when used in isolation.
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CITATION
S. Watt, B. Keshari, "Hybrid Mathematical Symbol Recognition Using Support Vector Machines", 2013 12th International Conference on Document Analysis and Recognition, vol. 02, no. , pp. 859-863, 2007, doi:10.1109/ICDAR.2007.136
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