Structural, Syntactic, and Statistical Pattern Recognition

Joint IAPR International Workshop, SSPR&SPR 2012, Hiroshima, Japan, November 7-9, 2012. Proceedings

  • Georgy Gimel’farb
  • Edwin Hancock
  • Atsushi Imiya
  • Arjan Kuijper
  • Mineichi Kudo
  • Shinichiro Omachi
  • Terry Windeatt
  • Keiji Yamada

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7626)

Table of contents

  1. Front Matter
  2. Pierre Devijver Award Lecture

  3. Invited Talks

  4. Structural, Syntactical, and Statistical Pattern Recognition

    1. Lin Han, Luca Rossi, Andrea Torsello, Richard C. Wilson, Edwin R. Hancock
      Pages 33-41
    2. Benoit Gaüzère, Luc Brun, Didier Villemin
      Pages 42-50
    3. Robert P. W. Duin, Ana L. N. Fred, Marco Loog, Elżbieta Pękalska
      Pages 51-59
    4. Zhouyu Fu, Guojun Lu, Kai-Ming Ting, Dengsheng Zhang
      Pages 60-69
  5. Graph and Tree Methods

    1. Lu Bai, Edwin R. Hancock
      Pages 79-88
    2. Xavier Cortés, Francesc Serratosa, Albert Solé-Ribalta
      Pages 98-106
    3. Nicola Rebagliati, Albert Solé-Ribalta, Marcello Pelillo, Francesc Serratosa
      Pages 107-115
  6. Randomized Methods and Image Analysis

    1. Silvio Jamil F. Guimarães, Jean Cousty, Yukiko Kenmochi, Laurent Najman
      Pages 116-125
    2. Martin Tschirsich, Arjan Kuijper
      Pages 126-134
    3. Jaume Gibert, Ernest Valveny, Horst Bunke, Alicia Fornés
      Pages 135-143
    4. Luca Rossi, Andrea Torsello, Edwin R. Hancock
      Pages 144-152
    5. Sergej Lewin, Xiaoyi Jiang, Achim Clausing
      Pages 153-161
  7. Kernel Methods in Structural and Syntactical Pattern Recognition

    1. Martin Tschirsich, Arjan Kuijper
      Pages 162-170
    2. Laura Antanas, Paolo Frasconi, Fabrizio Costa, Tinne Tuytelaars, Luc De Raedt
      Pages 171-180

About these proceedings


This volume constitutes the refereed proceedings of the Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012), held in Hiroshima, Japan, in November 2012 as a satellite event of the 21st International Conference on Pattern Recognition, ICPR 2012.
The 80 revised full papers presented together with 1 invited paper and the Pierre Devijver award lecture were carefully reviewed and selected from more than 120 initial submissions. The papers are organized in topical sections on structural, syntactical, and statistical pattern recognition, graph and tree methods, randomized methods and image analysis, kernel methods in structural and syntactical pattern recognition, applications of structural and syntactical pattern recognition, clustering, learning, kernel methods in statistical pattern recognition, kernel methods in statistical pattern recognition, as well as applications of structural, syntactical, and statistical methods.


collective classification genetic optimization kernel methods neural networks semantic parts

Editors and affiliations

  • Georgy Gimel’farb
    • 1
  • Edwin Hancock
    • 2
  • Atsushi Imiya
    • 3
  • Arjan Kuijper
    • 4
  • Mineichi Kudo
    • 5
  • Shinichiro Omachi
    • 6
  • Terry Windeatt
    • 7
  • Keiji Yamada
    • 8
  1. 1.Department of Computer ScienceUniversity of AucklandAucklandNew Zealand
  2. 2.Department of Computer ScienceUniversity of YorkYorkUK
  3. 3.Institute of Media and Information TechnologyChiba UniversityInage-kuJapan
  4. 4.Technische Universität/Fraunhofer IGDDarmstadtGermany
  5. 5.Graduate School of Information Science and TechnologyHokkaido UniversitySapporoJapan
  6. 6.Graduate School of EngineeringTohoku UniversitySendaiJapan
  7. 7.Centre for Vision, Speech and Signal ProcessingUniversity of SurreyGuildfordUK
  8. 8.C&C Innovation Research LaboratoriesNEC CorporationIkoma-ShiJapan

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2012
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-34165-6
  • Online ISBN 978-3-642-34166-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book
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