Case-based Reasoning on Images and Signals

by Perner, Petra

• ISBN13: 9783540731788
• ISBN10: 3540731784
• Format: Hardcover
• Copyright: 2007-11-03
• Publisher: Springer Verlag

Summary

This book is the first edited book that deals with the special topic of signals and images within Case-Based Reasoning (CBR). Signal-interpreting systems are becoming increasingly popular in medical, industrial, ecological, biotechnological and many other applications. Existing statistical and knowledge-based techniques lack robustness, accuracy and flexibility. New strategies are needed that can adapt to changing environmental conditions, signal variation, user needs and process requirements. Introducing CBR strategies into signal-interpreting systems can satisfy these requirements. CBR can be used to control the signal-processing process in all phases of a signal-interpreting system to derive information of the highest possible quality. Beyond this CBR offers different learning capabilities, for all phases of a signal-interpreting system, that satisfy different needs during the development process of a signal-interpreting system. The structure of the book is divided into a theoretical part and into an application-oriented part. Scientists and computer science experts from industry, medicine and biotechnology who like to work on the special topics of CBR for signals and images will find this work useful. Although case-based reasoning is often not a standard lecture at universities we hope we also inspire PhD students to deal with this topic.

Table of Contents

Introduction to Case-Based Reasoning for Signals and Images	p. 1
Similarity	p. 25
Distance Function Learning for Supervised Similarity Assessment	p. 91
Induction of Similarity Measures for Case Based Reasoning Through Separable Data Transformations	p. 127
Graph Matching	p. 149
Memory Structures and Organization in Case-Based Reasoning	p. 175
Learning a Statistical Model for Performance Prediction in Case-Based Reasoning	p. 195
A CBR Agent for Monitoring the Carbon Dioxide Exchange Rate from Satellite Images	p. 213
Extracting Knowledge from Sensor Signals for Case-Based Reasoning with Longitudinal Time Series Data	p. 247
Prototypes and Case-Based Reasoning for Medical Applications	p. 285
Case-Based Reasoning for Image Segmentation by Watershed Transformation	p. 319
Similarity-Based Retrieval for Biomedical Applications	p. 355
Medical Imagery in Case-Based Reasoning	p. 389
Instance-Based Relevance Feedback in Image Retrieval Using Dissimilarity Spaces	p. 419
Table of Contents provided by Blackwell. All Rights Reserved.