Overview

The neural network paradigm with its various advantages might be the next promising bridge between artificial intelligence and pattern recognition that will help with the conceptualization of new computational artifacts. This volume contains ten papers which represent some of the work being done in the field, such as in computational neuroscience, pattern recognition, computational vision and applications.

Full Product Details

Author:   Walter Karplus (Univ Of California, Los Angeles, Usa) ,  Josef Skrzypek (-)
Publisher:   World Scientific Publishing Co Pte Ltd
Imprint:   World Scientific Publishing Co Pte Ltd
Volume:   3
ISBN:  

9789810210144

ISBN 10:   9810210140
Pages:   224
Publication Date:   01 July 1992
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Lightness constancy from luminance contrast, J. Skrzypek and D. Gungner; bringing the grandmother back into the picture - a memory-based view of object recognition, S. Edelman and T. Poggio; internal organization of classifier networks trained by backpropagation, D.F. Michaels; system identification with artificial neural networks, E.R. Tisdale and W.J. Karplus; mixed finite element based neural networks in visual reconstruction, D. Suter; the random Neural network model for texture generation, V. Atalay, et al; neural networks for collective translational invariant object recognition, L.W. Chan; image recognition and reconstruction using associative magnetic processing, J.M. Goodwin, et al; incorporating uncertainty in neural networks, B.R. Kammerer; neural networks for the recognition of engraved musical scores, P. Martin and C. Bellissant.

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