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Table of Contents

I. Theory.- Neurobiological Background.- Related Work.- Neural Abstraction Pyramid Architecture.- Unsupervised Learning.- Supervised Learning.- II. Applications.- Recognition of Meter Values.- Binarization of Matrix Codes.- Learning Iterative Image Reconstruction.- Face Localization.- Summary and Conclusions.

Reviews

From the reviews: "This booklet is the reprint of a thesis. It addresses image interpretation using a neural network architecture mimicking the human visual system. … The exposition is divided in two parts, namely theory and applications. … In short this thesis is very interesting, well written and easy to read." (Jean Th. Lapresté, Zentralblatt MATH, Vol. 1041 (16), 2004)