Please use this identifier to cite or link to this item:
http://dspace.uniten.edu.my/jspui/handle/123456789/7846
DC Field | Value | Language |
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dc.contributor.author | Ahmad, A.R. | en_US |
dc.date.accessioned | 2018-01-17T07:47:19Z | - |
dc.date.available | 2018-01-17T07:47:19Z | - |
dc.date.issued | 2004 | - |
dc.identifier.uri | http://dspace.uniten.edu.my/jspui/handle/123456789/7846 | - |
dc.description.abstract | Discrete hidden Markov model (HMM) and hybrid of neural network (NN) and HMM are popular methods in handwritten word recognition system. The hybrid system gives better recognition result due to better discrimination capability of the NN [Y. Bengio et al., 1995]. Support vector machine (SVM) is an alternative to NN. In speech recognition (SR), SVM has been successfully used in the context of a hybrid SVM/HMM system. It gives a better recognition result compared to the system based on hybrid NN/HMM [A. Ganapathiraju, January 2002]. This paper describes the work in developing a hybrid SVM/HMM OHR system. Some preliminary experimental results of using SVM with RBF kernel on IRONOFF, UNIPEN and IRONOFF- UNIPEN character database are provided. | en_US |
dc.language.iso | en | en_US |
dc.subject | Handwriting recognition | en_US |
dc.subject | Support vector machines | en_US |
dc.subject | Hidden Markov models, | en_US |
dc.title | Online handwriting recognition using support vector machine | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.doi | 10.1109/TENCON.2004.1414419 | - |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
Appears in Collections: | CCI Scholarly Publication |
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