Recognition of unconstrained handwritten numerals by doubly self-organizing neural network

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

8 Citations (Scopus)

Abstract

In this paper we present an efficient pattern recognizer based on a self-organizing neural network which can adapt its structure as well as its weights. The network, called doubly self-organizing neural network (DSNN), makes use of the structure-adaptation capability to place the nodes of prototype vectors into the pattern space accurately so as to make the decision boundaries as close to the class boundaries as possible. In order to verify the superiority of the DSNN, experiments with the unconstrained handwritten numeral database of Concordia University in Canada were conducted. The proposed method has produced 96.05% of the recognition rate, which we show better than those of several previous methods reported in the literature on the same database.

Original languageEnglish
Title of host publicationTrack D
Subtitle of host publicationParallel and Connectionist Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages426-430
Number of pages5
ISBN (Print)081867282X, 9780818672828
DOIs
Publication statusPublished - 1996 Jan 1
Event13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria
Duration: 1996 Aug 251996 Aug 29

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume4
ISSN (Print)1051-4651

Other

Other13th International Conference on Pattern Recognition, ICPR 1996
CountryAustria
CityVienna
Period96/8/2596/8/29

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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    Cho, S. B. (1996). Recognition of unconstrained handwritten numerals by doubly self-organizing neural network. In Track D: Parallel and Connectionist Systems (pp. 426-430). [547602] (Proceedings - International Conference on Pattern Recognition; Vol. 4). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPR.1996.547602