© 2020

Artificial Neural Networks in Pattern Recognition

9th IAPR TC3 Workshop, ANNPR 2020, Winterthur, Switzerland, September 2–4, 2020, Proceedings

  • Frank-Peter Schilling
  • Thilo Stadelmann
Conference proceedings ANNPR 2020

Part of the Lecture Notes in Computer Science book series (LNCS, volume 12294)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 12294)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Invited Papers

    1. Front Matter
      Pages 1-1
    2. Pascal Paysan, Igor Peterlik, Toon Roggen, Liangjia Zhu, Claas Wessels, Jan Schreier et al.
      Pages 3-22
    3. Nikolaus Korfhage, Markus Mühling, Bernd Freisleben
      Pages 23-35
  3. Foundations

    1. Front Matter
      Pages 37-37
    2. Graham Spinks, Marie-Francine Moens
      Pages 39-51 Open Access
    3. Christoph Walter Senn, Itsuo Kumazawa
      Pages 77-88
    4. Ahmad Aghaebrahimian, Mark Cieliebak
      Pages 102-110
  4. Applications

    1. Front Matter
      Pages 111-111
    2. Albert Matveev, Alexey Artemov, Denis Zorin, Evgeny Burnaev
      Pages 113-124
    3. Stefan Glüge, Mohammadreza Amirian, Dandolo Flumini, Thilo Stadelmann
      Pages 125-137
    4. Tobias Ricken, Adrian Steinert, Peter Bellmann, Steffen Walter, Friedhelm Schwenker
      Pages 138-148
    5. Peter Bellmann, Patrick Thiam, Friedhelm Schwenker
      Pages 149-161
    6. Sina Famouri, Lia Morra, Fabrizio Lamberti
      Pages 162-172
    7. Fabian Furger, Ludovic Amruthalingam, Alexander Navarini, Marc Pouly
      Pages 187-199
    8. Moritz Kaufmann, Martin Schüle, Theo H. M. Smits, Joël F. Pothier
      Pages 200-210

About these proceedings


This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic.
The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.


artificial intelligence classification clustering clustering algorithms data security feature selection image processing image segmentation learning algorithms machine learning network architecture neural networks object recognition pattern recognition recurrent neural networks supervised learning Support Vector Machines (SVM)

Editors and affiliations

  1. 1.Zurich University of Applied Sciences ZHAWWinterthurSwitzerland
  2. 2.Zurich University of Applied Sciences ZHAWWinterthurSwitzerland

Bibliographic information