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Combining multiple classifiers based on statistical method for handwritten Chinese character recognition

  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In various application areas of pattern recognition, combining multiple classifiers is regarded as a new method for achieving a substantial gain in performance of systems. This paper presents a novel method for handwritten Chinese character recognition to combine multiple classifiers based on statistics. Fusion strategies are discussed for providing a basis for combining classifiers. These combination strategies are experimentally tested on online handwritten Chinese character recognition system. In our experiments, other combination approaches are also involved for comparison. Experiment results show that their effectiveness is considered.

Original languageEnglish
Title of host publication2002 International Conference on Machine Learning and Cybernetics, ICMLC 2002
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages252-255
Number of pages4
ISBN (Print)0780375084, 9780780375086
StatePublished - 2002
Externally publishedYes
Event1st International Conference on Machine Learning and Cybernetics, ICMLC 2002 - Beijing, China
Duration: 4 Nov 20025 Nov 2002

Publication series

NameProceedings of 2002 International Conference on Machine Learning and Cybernetics
Volume1

Conference

Conference1st International Conference on Machine Learning and Cybernetics, ICMLC 2002
Country/TerritoryChina
CityBeijing
Period4/11/025/11/02

Keywords

  • Combining multiple classifiers
  • Fusion strategies
  • Handwritten Chinese character recognition

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