Morphological hetero-associative memories applied to restore true-color patterns

Roberto A. Vázquez, Humberto Sossa

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

7 Citas (Scopus)

Resumen

Morphological associative memories (MAMs) are a special type of associative memory which exhibit optimal absolute storage capacity and one-step convergence. This associative model substitutes the additions and multiplications by additions/subtractions and maximums/minimums. This type of associative model has been applied to different pattern recognition problems including face localization and reconstruction of gray scale images. Despite of his power, it has not been applied to problems involving true-color patterns. In this paper we describe how a Morphological Hetero-associative Memory (MHAM) can be applied in problems that involve true-color patterns. In addition, a study of the behavior of this associative model in the reconstruction of true-color images is performed using a benchmark of 14400 images altered by different type of noises.

Idioma originalInglés
Título de la publicación alojadaAdvances in Neural Networks - ISNN 2009 - 6th International Symposium on Neural Networks, ISNN 2009, Proceedings
Páginas520-529
Número de páginas10
EdiciónPART 3
DOI
EstadoPublicada - 2009
Evento6th International Symposium on Neural Networks, ISNN 2009 - Wuhan, China
Duración: 26 may. 200929 may. 2009

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NúmeroPART 3
Volumen5553 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia6th International Symposium on Neural Networks, ISNN 2009
País/TerritorioChina
CiudadWuhan
Período26/05/0929/05/09

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