Online handwriting recognition using support vector machine
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 al...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Published: |
2004
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/7152/ http://dx.doi.org/10.1109/TENCON.2004.1414419 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1845471754972037120 |
|---|---|
| author | Ahmad, Abdul Rahim Khalid, Marzuki Viard-Gaudin, C. Poisson, E. |
| author_facet | Ahmad, Abdul Rahim Khalid, Marzuki Viard-Gaudin, C. Poisson, E. |
| author_sort | Ahmad, Abdul Rahim |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | 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. |
| format | Conference or Workshop Item |
| id | my.utm.eprints-7152 |
| institution | Universiti Teknologi Malaysia |
| publishDate | 2004 |
| record_format | eprints |
| spelling | my.utm.eprints-71522017-09-10T08:18:37Z http://eprints.utm.my/7152/ Online handwriting recognition using support vector machine Ahmad, Abdul Rahim Khalid, Marzuki Viard-Gaudin, C. Poisson, E. QA75 Electronic computers. Computer science 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. 2004 Conference or Workshop Item PeerReviewed Ahmad, Abdul Rahim and Khalid, Marzuki and Viard-Gaudin, C. and Poisson, E. (2004) Online handwriting recognition using support vector machine. In: IEEE Region 10 Annual International Conference, 21-24 Nov. 2004, Selangor. http://dx.doi.org/10.1109/TENCON.2004.1414419 |
| spellingShingle | QA75 Electronic computers. Computer science Ahmad, Abdul Rahim Khalid, Marzuki Viard-Gaudin, C. Poisson, E. Online handwriting recognition using support vector machine |
| title | Online handwriting recognition using support vector machine |
| title_full | Online handwriting recognition using support vector machine |
| title_fullStr | Online handwriting recognition using support vector machine |
| title_full_unstemmed | Online handwriting recognition using support vector machine |
| title_short | Online handwriting recognition using support vector machine |
| title_sort | online handwriting recognition using support vector machine |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/7152/ http://dx.doi.org/10.1109/TENCON.2004.1414419 |
| url_provider | http://eprints.utm.my/ |