Associative Memories Applied to Pattern Recognition

Authors:
Roberto A. Vazquez;Humberto Sossa
Affiliations:
Centro de Investigación en Computación-IPN, Av. Juan de Dios Batíz, esq. Miguel Othón de Mendizábal, Mexico City, Mexico 07738;Centro de Investigación en Computación-IPN, Av. Juan de Dios Batíz, esq. Miguel Othón de Mendizábal, Mexico City, Mexico 07738
Venue:
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Year:
2008

Citing 10
Cited 0

Support Vector Machines for 3D Object Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalizing Operations of Binary Autoassociative Morphological Memories Using Fuzzy Set Theory

Journal of Mathematical Imaging and Vision
Eigenfaces for recognition

Journal of Cognitive Neuroscience
A New Associative Model with Dynamical Synapses

Neural Processing Letters
Correlation Matrix Memories

IEEE Transactions on Computers
3D object recognition based on low frequency response and random feature selection

MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Associative memories applied to image categorization

CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Invariant descriptions and associative processing applied to object recognition under occlusions

MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Gray-scale morphological associative memories

IEEE Transactions on Neural Networks
Low frequency response and random feature selection applied to face recognition

ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition

Quantified Score

Hi-index	0.00

Visualization

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.