Off-line recognition of totally unconstrained handwritten numerals using multilayer cluster neural network

Seong Whan Lee, Young Joon Kim

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

1 Citation (Scopus)

Abstract

In this paper, we propose a simple multilayer cluster neural network with five independent subnetworks for off-line recognition of totally unconstrained handwritten numerals. We also show that the use of genetic algorithms for avoiding the problem of finding local minima in training the multilayer cluster neural network with gradient descent technique reduces error rates.

Original languageEnglish
Title of host publicationProceedings of the 12th IAPR International Conference on Pattern Recognition - Conference B
Subtitle of host publicationPattern Recognition and Neural Networks, ICPR 1994
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages507-509
Number of pages3
ISBN (Electronic)0818662700
Publication statusPublished - 1994
Externally publishedYes
Event12th IAPR International Conference on Pattern Recognition - Conference B: Pattern Recognition and Neural Networks, ICPR 1994 - Jerusalem, Israel
Duration: 1994 Oct 91994 Oct 13

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2
ISSN (Print)1051-4651

Conference

Conference12th IAPR International Conference on Pattern Recognition - Conference B: Pattern Recognition and Neural Networks, ICPR 1994
Country/TerritoryIsrael
CityJerusalem
Period94/10/994/10/13

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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