Case-Based Reasoning on Images and Signals

  • Petra Perner

Part of the Studies in Computational Intelligence book series (SCI, volume 73)

Table of contents

  1. Front Matter
    Pages I-X
  2. M. M. Richter
    Pages 25-90
  3. A. Bagherjeiran, C. F. Eick
    Pages 91-126
  4. X. Jiang, H. Bunke
    Pages 149-173
  5. R. Schmidt, T. Waligora, O. Vorobieva
    Pages 285-317
  6. M. Frucci, P. Perner, G. Sanniti di Baja
    Pages 319-353
  7. L. G. Shapiro, I. Atmosukarto, H. Cho, H. J. Lin, S. Ruiz-Correa, J. Yuen
    Pages 355-387
  8. D. C. Wilson, D. O’Sullivan
    Pages 389-418

About this book

Introduction

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 to also inspire PhD students to deal with this topic.

Keywords

Case-Based Reasoning Signal Statistica classification computational intelligence image processing image segmentation intelligence learning memory model multimedia performance signal processing transformation

Editors and affiliations

  • Petra Perner
    • 1
  1. 1.Institute of Computer Vision and Applied Computer SciencesIBaILeipzigGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-73180-1
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-73178-8
  • Online ISBN 978-3-540-73180-1
  • Series Print ISSN 1860-949X
  • About this book