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  4. Structural, syntactic, and statistical pattern recognition. Joint IAPR International Workshop, SSPR & SPR 2012
 
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2012
Conference Proceeding
Title

Structural, syntactic, and statistical pattern recognition. Joint IAPR International Workshop, SSPR & SPR 2012

Title Supplement
Hiroshima, Japan, November 7-9, 2012; proceedings
Abstract
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.
Editor(s)
Gimel'farb, Georgy
Univ. of Auckland
Hancock, Edwin
Univ. of York
Imiya, Atsushi
Chiba University
Kuijper, Arjan  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Kudo, Mineichi
Hokkaido University
Omachi, Shinichiro
Tohoku University
Windeatt, Terry
Univ. of Surrey
Yamada, Keiji
NEC Corporation, Japan
Corporate Author
International Association for Pattern Recognition -IAPR-
Publisher
Springer  
Publishing Place
Berlin
Conference
International Workshops on Structural and Syntactic Pattern Recognition (SSPR) 2012  
International Workshops on Statistical Techniques in Pattern Recognition (SPR) 2012  
DOI
10.1007/978-3-642-34166-3
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • classification

  • optimization

  • neural network

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