Liked-BAM neural network for image recognition

D. G. Shen, F. H. Qi

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

Abstract

A neural network model and its application to image recognition are proposed in this paper. This model consists of Mapping Network (MN) and Liked Bidirectional Associative Memory (LBAM). Invariant mapping is used in MN in order to decrease the number of dimensions of image samples and not to change the distance between them. LBAM's structure is simple and its convergence speed is fast. Several computer simulations given to prove that the model is capable of recognizing noise - added targets and targets cut off little part.

Original languageEnglish
Title of host publicationProc 1993 IEEE Reg 10 Conf Comput Commun Control Power Eng (TENCON '93)
Editors Anon
PublisherPubl by IEEE
Pages966-968
Number of pages3
ISBN (Print)0780312333
Publication statusPublished - 1993
Externally publishedYes
EventProceedings of the 1993 IEEE Region 10 Conference on Computer, Communication, Control aand Power Engineering. Part 3 (of 5) - Beijing, China
Duration: 1993 Oct 191993 Oct 21

Publication series

NameProc 1993 IEEE Reg 10 Conf Comput Commun Control Power Eng (TENCON '93)

Other

OtherProceedings of the 1993 IEEE Region 10 Conference on Computer, Communication, Control aand Power Engineering. Part 3 (of 5)
CityBeijing, China
Period93/10/1993/10/21

ASJC Scopus subject areas

  • Engineering(all)

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