Skip to product information
1 of 1

Progress in Neural Networks, Volume Six

Regular price £52.95
Sale price £52.95 Regular price £52.95
Sale Sold out
Neural network applications have had tremendous growth in the last few years, and pattern recognition played a key role in many areas. One of the more focused areas is shape recognition. The purpo...
Read More
  • Format:
  • 01 May 1999
View Product Details

Neural network applications have had tremendous growth in the last few years, and pattern recognition played a key role in many areas. One of the more focused areas is shape recognition.

The purpose of this book is to provide the reader with a fresh perspective on the research. While "Volume 6" in the series should not be construed as an exhaustive collection of the work that has taken place, it represents some of the mainstream works with some international flavor. The shape recognition problem is addressed from several different perspectives here, to show that the theoretical discoveries in neural networks have a profound effect on the broadening of applications.

This long-standing series reviews current research in natural and synthetic networks as well as reviewing state-of-the-art research in modelling, analysis, design, and development of neural networks in software and hardware areas. The contributions from leading researchers and practitioners shape academic and professional programs in this area, and serve as a platform for detailed and expanded discussion of topics of interest to the neural network and cognitive information processing communities. This is directly aimed at those professionally involved in networks research, such as lecturers and primary investigators in neural computing, learning, and memory.

files/i.png Icon
Price: £52.95
Pages: 200
Publisher: Intellect Books
Imprint: Intellect Books
Publication Date: 01 May 1999
ISBN: 9781567503289
Format: Hardcover
BISACs:

COMPUTERS / General, Information technology: general topics

REVIEWS Icon

Cortical Images, Self-Organizing Neural Networks and Object Classification               3

Nikolay Petkov

 

Parallel Implementation of a Neural Network Ensemble on the Connection Machine               45

Daijin Kim

Minsoo Suk

 

Boolean Neural Networks Trained with Simulated Annealing               85

Jarkko Niittylahti

 

On the Computational Complexity of Analyzing the Hopfield-Clique Network               103

Arun Jagota

 

A Harmony-Maximisation Network Implementation of a Compound Labeling Scheme

for Scene Analysis               119

Tatiana Tambouratzis

 

Optimal Image Boundary via Hopfield Net and Tunneling               161

William Cheung

Roland Chin

Tong Lee

 

Shape Matching Based on Invariants               209

Stan Z. Li