Face recognition using some aspects of the infant vision system and associative memories

Roberto A. Vazquez, Humberto Sossa, Beatriz A. Garro

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

1 Scopus citations

Abstract

Several associative memories (AM) have been proposed in the last years. These AMs have several constraints that limit their applicability in complex problems such as face recognition. Despite of the power of these models, they cannot reach its full power without applying new mechanisms based on current and future studies on biological neural networks. In this research we show how a network of dynamic associative memories (DAM) combined with some aspects of the infant vision system could be efficiently applied to the face recognition problem. Through several experiments by using a benchmark of faces the accuracy of the proposal is tested. © Springer-Verlag Berlin Heidelberg 2007.
Original languageAmerican English
Title of host publicationFace recognition using some aspects of the infant vision system and associative memories
Pages437-446
Number of pages392
ISBN (Electronic)9783540767244
StatePublished - 1 Dec 2007
EventLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -
Duration: 1 Jan 2014 → …

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4756 LNCS
ISSN (Print)0302-9743

Conference

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Period1/01/14 → …

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Vazquez, R. A., Sossa, H., & Garro, B. A. (2007). Face recognition using some aspects of the infant vision system and associative memories. In Face recognition using some aspects of the infant vision system and associative memories (pp. 437-446). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4756 LNCS).