A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
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 classification. Probabilistic outputs from the two support vector machine based multi-class classifiers running in parallel are combined by taking a weighted sum. Results from the experiments show that giving slightly higher weight to the on-line information produces betterdoi:10.1109/icdar.2007.4377037 dblp:conf/icdar/KeshariW07 fatcat:74j4fphdznhsvgmznzzq7f3qr4