© 2008

Applied Pattern Recognition

  • Horst Bunke
  • Abraham Kandel
  • Mark Last

Part of the Studies in Computational Intelligence book series (SCI, volume 91)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Face Recognition Applications

    1. Xiaoyi Jiang, Yung-Fu Chen
      Pages 29-48
    2. Kazunori Okada, Christoph von der Malsburg
      Pages 49-74
  3. Spatio-Temporal Patterns

    1. Amer Abufadel, Tony Yezzi, Ronald W. Schafer
      Pages 77-100
    2. Sigal Elnekave, Mark Last, Oded Maimon
      Pages 101-128
  4. Graph-Based Methods

    1. Horst Bunke, Peter Dickinson, Miro Kraetzl, Michel Neuhaus, Marc Stettler
      Pages 131-154
    2. Günter Westphal, Christoph von der Malsburg, Rolf P. Würtz
      Pages 155-199
  5. Special Applications

About this book


A sharp increase in the computing power of modern computers, accompanied by a decrease in the data storage costs, has triggered the development of extremely powerful algorithms that can analyze complex patterns in large amounts of data within a very short period of time. Consequently, it has become possible to apply pattern recognition techniques to new tasks characterized by tight real-time requirements (e.g., person identification) and/or high complexity of raw data (e.g., clustering trajectories of mobile objects). The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.


Markov Statistica Wavelet algorithm algorithms calculus cognition complexity computational intelligence image processing intelligence model object recognition pattern pattern recognition

Editors and affiliations

  • Horst Bunke
    • 1
  • Abraham Kandel
    • 2
  • Mark Last
    • 3
  1. 1.Institute of Computer Science and Applied MathematicsSwitzerland
  2. 2.University of South FloridaTampaUSA
  3. 3.Ben-Gurion University of the NegevIsrael

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