基于知识的图像处理系统(英文版) pdf 夸克云 tct umd 下载 2025 azw3 kindle

This book is aimed at final year and postgraduate students with some background in computer science, and researchers requiring a brief introduction to

either area: knowledge-based systems or image processing. The book is in three parts, parts 1 and 2 are designed to provide overviews of each of the areas (each part equating to a half semester course), part III giyes a report on current work in which the two converge before describing some of the issues involved in designing future knowledge-based image processing systems. Sample questi*** are also provided for parts 1 and 2 in an appendix (A).

This book attempts to give an insight into the two areas of research and current systems, and suggests a way forward for designing future systems.

Preface

Acknowledgements

Contributors

Part 1: Knowledge-Based Systems: An Overview

D. Graham and D. Martland

1 Introduction to Knowledge-Based Systems

1.1 Background to Knowledge-Based Systems

1.1.1 Search Strategies

1.2 What is a Knowledge-Based System?

1.2.1 Basic Architecture

1.2.2 Characteristics of an Expert System

1.2.3 Explaining Soluti***

1.2.4 Uncertainty

1.2.5 Evaluating Expert Systems Generally

2 Knowledge-Based System Architectures and Applicati***

2.1 Knowledge-Based System Tools and Architectures

2.1.1 Expert System Shells

2.1.2 High-Level Programming Languages

2.1.3 Hybrid Systems

2.1.4 Skeletal Systems

2.1.5 Truth Maintenance Systems

2.1.6 Current Research Problems in Expert Systems

2.1.7 Professional Issues

2.2 Knowledge-Based System Applicati***

2.2.1 Early Systems

2.2.2 Current Systems

3 Knowledge Elicitation

3.1 Knowledge Acquisition and Knowledge Elicitation

3.2 Stages of Knowledge Acquisition

3.3 Knowledge Acquisition Methodologies

3.3.1 Machine-Aided Knowledge Acquisition

3.3.2 Human-Labour Oriented Approaches to Knowledge Elicitation

3.4 Knowledge Elicitation Techniques

3.5 Knowledge Elicitation Issues

3.6 Knowledge Acquisition Tools:TEIRESIAS and OPAL

4 Knowledge Representation

4.1 Schemes for Representing Knowledge

4.2 Issues in Knowledge Representation

4.3 Logical Representation Schemes

4.4 Procedural Representation Schemes:Production Systems

4.5 Network Representati***: Semantic Networks

4.6 Structured Representati***

4.6.1 Conceptual Dependency Theory

4.6.2 Frames

4.6.3 Scripts

4.*** Objects

5 Neural Networks

5.1 Introduction

5.2 Background to Neural Networks

5.2.1 Motivation

5.2.2 Biological Neur***

5.3 Feed-Forward Networks

5.4 Applying Neural Network Methods

5.5 Feed-Back Networks

5.5.1 La***l Inhibition

5.5.2 Hopfietd Networks

5.6 Kohonen Networks

5.7 Software Support for Neural Networks

5.8 Hardware Support for Neural Networks

5.9 Image Processing Applicati***

5.10 Strategies for Developing Applicati***

Part 2: Image Processing: An Overview

A. Barrett

6 Introduction to Image Processing

6.1 Background

……

Part 3:Knowledge-Based Systems and Image Processing:D.Graham and A.Barrett

Appendix A:Exercises and Further Reading

References

Author Index

Subject Index

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