Associative memories applied to pattern recognition

Roberto A. Vazquez, Humberto Sossa

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

2 Scopus citations

Abstract

An associative memory (AM) is a special kind of neural network that allows associating an output pattern with an input pattern. In the last years, several associative models have been proposed by different authors. However, they have several constraints which limit their applicability in complex pattern recognition problems. In this paper we gather different results provided by a dynamic associative model and present new results in order to describe how this model can be applied to solve different complex problems in pattern recognition such as object recognition, image restoration, occluded object recognition and voice recognition.

Original languageEnglish
Title of host publicationArtificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings
Pages111-120
Number of pages10
EditionPART 2
DOIs
StatePublished - 2008
Event18th International Conference on Artificial Neural Networks, ICANN 2008 - Prague, Czech Republic
Duration: 3 Sep 20086 Sep 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5164 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Artificial Neural Networks, ICANN 2008
Country/TerritoryCzech Republic
CityPrague
Period3/09/086/09/08

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