Handwritten digit classification based on Alpha-Beta Associative Model

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6 Scopus citations

Abstract

In this paper we present a new model appropriate for pattern recognition tasks. This new model, called αβ Associative Model, arises when taking theoretical elements from the αβ associative memories, and they are merged with several new mathematical transforms. When applied to handwritten digits recognition, namely in the MNIST database, the αβ Associative Model exhibits competitive results against some of the most widely known algorithms currently available in scientific literature.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, Proceedings
Pages437-444
Number of pages8
DOIs
StatePublished - 2008
Externally publishedYes
Event13th Iberoamerican Congress on Pattern Recognition, CIARP 2008 - Havana, Cuba
Duration: 9 Sep 200812 Sep 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5197 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th Iberoamerican Congress on Pattern Recognition, CIARP 2008
Country/TerritoryCuba
CityHavana
Period9/09/0812/09/08

Keywords

  • Alpha-Beta associative model
  • Handwritten digits classification
  • MNIST database

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