Progress in Neural Networks, Volume Six
Intellect Books (Verlag)
978-1-56750-328-9 (ISBN)
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The purpose of this book is to provide the reader with a fresh perspective on the research.
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.
Dr. Omid Omidvar is acting Director of the Program and Information Management Office, and works as a technology analyst in Advanced Technology Program (ATP). Previously, he was the technical director of the SPPARC facility funded by the National Science Foundation in Washington, DC. He has also conducted research on NASA on the design of the neurocontroller for robotics arms, and was the Chief Technology Officer of Technology Research International.
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
Erscheint lt. Verlag | 1.5.1999 |
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Sprache | englisch |
Themenwelt | Geisteswissenschaften ► Psychologie ► Biopsychologie / Neurowissenschaften |
Mathematik / Informatik ► Informatik | |
Studium ► 1. Studienabschnitt (Vorklinik) ► Anatomie / Neuroanatomie | |
Naturwissenschaften ► Biologie ► Humanbiologie | |
Schlagworte | Progress in Neural Networks |
ISBN-10 | 1-56750-328-4 / 1567503284 |
ISBN-13 | 978-1-56750-328-9 / 9781567503289 |
Zustand | Neuware |
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