We explore a new approach to shape recognition based on a virtually infinite family of binary
features (queries) of the image data, designed to accommodate prior information about …

The Handbook of Neural Computation is a practical, hands-on guide to the design and
implementation of neural networks used by scientists and engineers to tackle difficult and/or …

An overview of automated recognition of partial discharges (PD) is given. The selection of
PD patterns, extraction of relevant information for PD recognition and the structure of a data …

In this paper, a new approach to computer supported diagnosis of skin tumors in
dermatology is presented. High resolution skin surface profiles are analyzed to recognize …

A comprehensive classifier system is presented for short-duration oceanic signals obtained
from passive sonar, which exhibit variability in both temporal and spectral characteristics …

Empire and Golden Delicious apples were classified based on their surface quality
conditions using backpropagation neural networks (BPNN) and statistical classifiers such as …

Human brain activities—electroencephalogram (EEG) signals—are likely to provide a
secure biometric approach for user identification because they are more sensitive, secretive …

While particulate products are often characterized by their median diameter or the width of
the particle size distribution, information is rarely given about the agglomeration degree of …

This paper presents a statistical approach to solve the problem of model selection, or
determine the number of hidden units for artificial neural networks. The authors' approach …

The backpropagation method is very sensitive to initial weights. A commonly used heuristic
is to train a large number of networks using different initial weights for training. The network …