Kernel methods and support vector machines for handwriting recognition

Abd Rahim Ahmad, M. Khalid, R. Yusof

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper presents a review of kernel methods in machine learning. The support vector machine (SVM) as one of the methods in machine learning to make use of kernels is first discussed with the intention of applying it to handwriting recognition. SVM works by mapping training data for a classification task into a higher dimensional feature space using the kernel function and then finding a maximal margin hyperplane, which separates the mapped data. Finding the solution hyperplane involves using quadratic programming which is computationally intensive. Algorithms for practical implementation such as sequential minimization optimization (SMO) and its improvements are discussed. A few simpler methods similar to SVM but requiring simpler computation are also mentioned for comparison. Usage of SVM for handwriting recognition is then proposed.

Original languageEnglish
Title of host publication2002 Student Conference on Research and Development
Subtitle of host publicationGlobalizing Research and Development in Electrical and Electronics Engineering, SCOReD 2002 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages309-312
Number of pages4
ISBN (Electronic)0780375653, 9780780375659
DOIs
Publication statusPublished - 01 Jan 2002
EventStudent Conference on Research and Development, SCOReD 2002 - Shah Alam, Malaysia
Duration: 16 Jul 200217 Jul 2002

Publication series

Name2002 Student Conference on Research and Development: Globalizing Research and Development in Electrical and Electronics Engineering, SCOReD 2002 - Proceedings

Other

OtherStudent Conference on Research and Development, SCOReD 2002
CountryMalaysia
CityShah Alam
Period16/07/0217/07/02

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Education

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    Ahmad, A. R., Khalid, M., & Yusof, R. (2002). Kernel methods and support vector machines for handwriting recognition. In 2002 Student Conference on Research and Development: Globalizing Research and Development in Electrical and Electronics Engineering, SCOReD 2002 - Proceedings (pp. 309-312). [1033120] (2002 Student Conference on Research and Development: Globalizing Research and Development in Electrical and Electronics Engineering, SCOReD 2002 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SCORED.2002.1033120