Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Generalizing Operations of Binary Autoassociative Morphological Memories Using Fuzzy Set Theory
Journal of Mathematical Imaging and Vision
Reconstruction of Patterns from Noisy Inputs Using Morphological Associative Memories
Journal of Mathematical Imaging and Vision
A Bidirectional Hetero-Associative Memory for True-Color Patterns
Neural Processing Letters
A New Associative Model with Dynamical Synapses
Neural Processing Letters
IEEE Transactions on Computers
Associative memories applied to image categorization
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
On fuzzy associative memory with multiple-rule storage capacity
IEEE Transactions on Fuzzy Systems
Implicative Fuzzy Associative Memories
IEEE Transactions on Fuzzy Systems
Morphological associative memories
IEEE Transactions on Neural Networks
Gray-scale morphological associative memories
IEEE Transactions on Neural Networks
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Median associative memories (MED-AMs) are a special type of associative memory based on the median operator This type of associative model has been applied to the restoration of gray scale images and provides better performance than other models, such as morphological associative memories, when the patterns are altered with mixed noise Despite of his power, MED-AMs have not been applied in problems involving true-color patterns In this paper we describe how a median hetero-associative memory (MED-HAM) could be applied in problems that involve true-color patterns A complete study of the behavior of this associative model in the restoration of true-color images is performed using a benchmark of 14400 images altered by different type of noises Furthermore, we describe how this model can be applied to an image categorization problem.