Computational Intelligence for Pattern Recognition

  • Witold Pedrycz
  • Shyi-Ming Chen

Part of the Studies in Computational Intelligence book series (SCI, volume 777)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Derek T. Anderson, Grant J. Scott, Muhammad Aminul Islam, Bryce Murray, Richard Marcum
    Pages 1-28
  3. Monica Bianchini, Giovanna Maria Dimitri, Marco Maggini, Franco Scarselli
    Pages 29-51
  4. Alessio Martino, Alessandro Giuliani, Antonello Rizzi
    Pages 53-81
  5. Peter Bellmann, Patrick Thiam, Friedhelm Schwenker
    Pages 83-113
  6. Khalil Laghmari, Christophe Marsala, Mohammed Ramdani
    Pages 115-164
  7. Wei Yan, Bob Zhang
    Pages 207-225
  8. Andre Vieira Pigatto, Alexandre Balbinot
    Pages 227-252
  9. Aunnoy K Mutasim, Rayhan Sardar Tipu, M. Raihanul Bashar, Md. Kafiul Islam, M. Ashraful Amin
    Pages 291-320
  10. Berat A. Erol, Abhijit Majumdar, Jonathan Lwowski, Patrick Benavidez, Paul Rad, Mo Jamshidi
    Pages 369-395
  11. Farika T. Putri, Mochammad Ariyanto, Wahyu Caesarendra, Rifky Ismail, Kharisma Agung Pambudi, Elta Diah Pasmanasari
    Pages 397-426
  12. Back Matter
    Pages 427-428

About this book


The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.


Computational Intelligence Pattern Recognition Fuzzy Pattern Recognition Pattern Classifiers Deep Learning

Editors and affiliations

  • Witold Pedrycz
    • 1
  • Shyi-Ming Chen
    • 2
  1. 1.University of AlbertaEdmontonCanada
  2. 2.National Taiwan University of Science and TechnologyTaipeiTaiwan

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-319-89628-1
  • Online ISBN 978-3-319-89629-8
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site