In this document we review and compare some of the classical and modern techniques for
solving the problem of invariant pattern recognition. Such techniques include integral …

Neural networks are a computing paradigm that is finding increasing attention among
computer scientists. In this book, theoretical laws and models previously scattered in the …

Human performance in visual perception by far exceeds the performance of contemporary
computer vision systems. While humans are able to perceive their environment almost …

This article presents some efficient training algorithms, based on first-order, second-order,
and conjugate gradient optimization methods, for a class of convolutional neural networks …

The present work is an attempt to develop a robust character recognizer for Telugu texts. We
aim at designing a recognizer, which exploits the inherent characteristics of the Telugu …

This paper proposes a new method for the design, through simulated evolution, of
biologically inspired receptive fields in feedforward neural networks (NNs). The method is …

Fukushima's (1988; 1989; 1992; 1993) neocognitron model is well-known for its
performance in visual pattern recognition. Through a training process, the visual pattern …

We describe a sequence of experiments investigating the strengths and limitations of
Fukushima's neocognitron as a handwritten digit classifier. Using the results of these …

We present a multilayer hierarchical neural system for automatic classification of complex
contour patterns. The system consists of a neocognitron-like network structure combined …

The paper describes a new method to incorporate biologically inspired receptive fields in
feedforward neural networks to enhance pattern recognition performance. We propose a …