Behaviour-based clustering of neural networks applied to document enhancement

Authors:
F. Zamora-Martínez;S. España-Boquera;M. J. Castro-Bleda
Affiliations:
Departamento de Lenguajes y Sistemas Informáticos, Universitat Jaume I, Castellón, Spain;Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Valencia, Spain;Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Valencia, Spain
Venue:
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Year:
2007

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Abstract

This work proposes an agglomerative hierarchical clustering algorithm where the items to be clustered are supervised-learning classifiers. The measure of similarity to compare classifiers is based on their behaviour. This clustering algorithm has been applied to document enhancement: A set of neural filters is trained with multilayer perceptrons for different types of noise and then clustered into groups to obtain a reduced set of neural clustered filters. In order to automatically determine which clustered filter is the most suitable to clean and enhance a real noisy image, an image classifier is also trained using multilayer perceptrons.