Applications of Neural Networks
Applications of Neural Networks gives a detailed description of 13 practical applications of neural networks, selected because the tasks performed by the neural networks are real and significant. The contributions are from leading researchers in neural ne
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APPLICATIONS OF NEURAL NETWORKS Edited by
ALAN F. MURRAY The University of Edinburgh
Springer Science+Business Media, LLC
A C.I.P. Catalogue record for this book is available from the Ubrary of Congress.
ISBN 978-1-4419-5140-3 ISBN 978-1-4757-2379-3 (eBook) DOI 10.1007/978-1-4757-2379-3
Printed on acid-free paper
All Rights Reserved
© 1995 Springer Science+Business Media New York Originally published by Kluwer Academic Publishers in 1995 Softcover reprint of the hardcover 1st edition 1995
No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without written permission from the copyright owner.
DEDICATION
To Peter LeComber- who was an open-minded sceptic. He was just beginning to believe in this neural stuff.
CONTENTS PREFACE
xi
SECTION A -INTRODUCTION 1
Neural Architectures and Algorithms Alan Murray ...................................................................................... ! 1. 2. 3. 4. 5. 6.
Introduction The Single Layer Perceptron (SLP) The Multi-Layer Perceptron (MLP) Radial Basis Function Networks Kohonen's Self-Organising Feature Map Networks Alternative Training Approaches for Layered Networks 7. Swnmary
1 2 8 14 17 21 28
SECTION B - SUPERVISED TRAINING Bl: Pattern Recognition and Classification
2
Face Finding in Images John M. Vincent ............................................................................... 35
1. Introduction 2. 3. 4. 5.
3
Generation of Feature Maps Feature Location in the High Resolution Image Experiments with Freshly Grabbed Sequences Conclusions
35 37 53
58 58
Sex Recognition from Faces Using Neural Networks B. Golomb, T. Sejnowski .................................................................. 11 1. 2. 3. 4.
Introduction Methods Results Discussion
71 75 82 83
viii
B2 :Diagnosis and Monitoring
4
ANN Based Classification of Arrhythmias M. Jabri, S. Pickard, P. Leong, Z. Chi, E. Tinker, R. Coggins and B. Flower ................................................................ 93 1. 2. 3. 4. 5. 6.
5
93 96 98 106
107 111
Classification of Cells in Cervical Smears Mathilde E. Boon and L.P. Kok ..................................................... 113 1. 2. 3. 4. 5. 6. 7. 8.
6
Introduction Data, Preprocessing and Feature Extraction Single Chamber Classification Dual Chamber Based Oassification Microelectonic Implementations Conclusions
The Need for Automatic Prescreening Application of Artificial Neural Networks The PAPNET System Devising a Working Protocol for P APNET-Assisted Screening PAPNET-Assisted Screening Versus Conventional Screening Practical Implications of P APNET-Assisted Screening PAPNET-Assisted Rescreening for Quality Control P APNET for Detection of Cancer Cells in False-Negative Smears
113 114 115 116 118 120 121 122
Multiphase flow monitoring in oil pipelines ChrisM. Bishop .................................................................
