Associative memories applied to image categorization

Roberto A. Vázquez, Humberto Sossa

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

10 Scopus citations

Abstract

In this paper we describe how associative memories can be applied to categorize images. If we present to an associative memory (AM) an image we would expect that the AM would respond with something that describes the content of the image; for example, if the image contains a tiger we would expect that the AM would respond with the word "tiger". In order to achieve this goal, we first chose a set of images. Each image is next associated to the word that better describes the content of the image. With this information an AM is trained as in [10]. We then use the AM to categorize instances of images with the same content even if these images are distorted by some kind of noise. The accuracy of the proposal is tested using a set of images containing different species of flowers and animals.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 11th Iberoamerican Congress in Pattern Recognition, CIARP 2006, Proceedings
PublisherSpringer Verlag
Pages549-558
Number of pages10
ISBN (Print)3540465561, 9783540465560
DOIs
StatePublished - 2006
Event11th Iberoamerican Congress in Pattern Recognition, CIARP 2006 - Cancun, Mexico
Duration: 14 Nov 200617 Nov 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4225 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th Iberoamerican Congress in Pattern Recognition, CIARP 2006
Country/TerritoryMexico
CityCancun
Period14/11/0617/11/06

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