Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings

A. Robles-Kelly (Editor), Marco Loog (Editor), B. Biggio (Editor), F. Escolano (Editor), R Wilson (Editor)

Research output: Book/ReportBook editingScientificpeer-review

Abstract

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural Syntactic, and Statistical Pattern Recognition, S+SSPR 2016, consisting of the International Workshop on Structural and Syntactic Pattern Recognition SSPR, and the International Workshop on Statistical Techniques in Pattern Recognition, SPR. The 51 full papers presented were carefully reviewed and selected from 68 submissions. They are organized in the following topical sections: dimensionality reduction, manifold learning and embedding methods; dissimilarity representations; graph-theoretic methods; model selection, classification and clustering; semi and fully supervised learning methods; shape analysis; spatio-temporal pattern recognition; structural matching; text and document analysis.
Original languageEnglish
Place of PublicationCham
PublisherSpringer
Number of pages378
ISBN (Electronic)978-3-319-49055-7
ISBN (Print)978-3-319-49054-0
DOIs
Publication statusPublished - 2016

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10029
ISSN (Electronic)0302-9743

Keywords

  • complex networks
  • machine learning
  • optimization
  • semantic segmentation
  • visualization
  • artificial intelligence
  • biometrics
  • database query processing and optimization
  • graph mining
  • graph theory and discrete mathematics
  • image classification
  • information storage and retrieval
  • information systems
  • multi-label classification
  • nonlinear embedding
  • object tracking
  • probabilistic inference problems
  • programming techniques
  • semi-supervised learning
  • structural SV

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