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  • Conference proceedings
  • © 2020

Artificial Neural Networks in Pattern Recognition

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

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

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Conference series link(s): ANNPR: IAPR Workshop on Artificial Neural Networks in Pattern Recognition

Conference proceedings info: ANNPR 2020.

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Table of contents (24 papers)

  1. Front Matter

    Pages i-xi
  2. Invited Papers

    1. Front Matter

      Pages 1-1
    2. Deep Learning Methods for Image Guidance in Radiation Therapy

      • Pascal Paysan, Igor Peterlik, Toon Roggen, Liangjia Zhu, Claas Wessels, Jan Schreier et al.
      Pages 3-22
    3. Intentional Image Similarity Search

      • Nikolaus Korfhage, Markus Mühling, Bernd Freisleben
      Pages 23-35
  3. Foundations

    1. Front Matter

      Pages 37-37
    2. Structured (De)composable Representations Trained with Neural Networks

      • Graham Spinks, Marie-Francine Moens
      Pages 39-51Open Access
    3. Abstract Echo State Networks

      • Christoph Walter Senn, Itsuo Kumazawa
      Pages 77-88
    4. Named Entity Disambiguation at Scale

      • Ahmad Aghaebrahimian, Mark Cieliebak
      Pages 102-110
  4. Applications

    1. Front Matter

      Pages 111-111
    2. Geometric Attention for Prediction of Differential Properties in 3D Point Clouds

      • Albert Matveev, Alexey Artemov, Denis Zorin, Evgeny Burnaev
      Pages 113-124
    3. How (Not) to Measure Bias in Face Recognition Networks

      • Stefan Glüge, Mohammadreza Amirian, Dandolo Flumini, Thilo Stadelmann
      Pages 125-137
    4. Feature Extraction: A Time Window Analysis Based on the X-ITE Pain Database

      • Tobias Ricken, Adrian Steinert, Peter Bellmann, Steffen Walter, Friedhelm Schwenker
      Pages 138-148
    5. Pain Intensity Recognition - An Analysis of Short-Time Sequences in a Real-World Scenario

      • Peter Bellmann, Patrick Thiam, Friedhelm Schwenker
      Pages 149-161
    6. A Deep Learning Approach for Efficient Registration of Dual View Mammography

      • Sina Famouri, Lia Morra, Fabrizio Lamberti
      Pages 162-172
    7. Applications of Generative Adversarial Networks to Dermatologic Imaging

      • Fabian Furger, Ludovic Amruthalingam, Alexander Navarini, Marc Pouly
      Pages 187-199
    8. Typing Plasmids with Distributed Sequence Representation

      • Moritz Kaufmann, Martin Schüle, Theo H. M. Smits, Joël F. Pothier
      Pages 200-210

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  1. Artificial Neural Networks in Pattern Recognition

About this book

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.

Editors and Affiliations

  • Zurich University of Applied Sciences ZHAW, Winterthur, Switzerland

    Frank-Peter Schilling, Thilo Stadelmann

Bibliographic Information

Buy it now

Buying options

eBook USD 49.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 64.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access