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Structural, syntactic, and statistical pattern recognition : joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29-December 2, 2016, Proceedings / Antonio Robles-Kelly, Marco Loog, Battista Biggio, Francisco Escolano, Richard Wilson (eds.).

Contributor(s): Material type: TextTextSeries: Lecture notes in computer science ; 10029. | LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics.Publisher: Cham, Switzerland : Springer, 2016Description: 1 online resource (xiii, 588 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319490557
  • 3319490559
  • 3319490540
  • 9783319490540
Other title:
  • S+SSPR 2016
Subject(s): Genre/Form: Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.4 23
LOC classification:
  • TK7882.P3
Online resources:
Contents:
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.
Summary: 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.
Holdings
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International conference proceedings.

Includes author index.

Online resource; title from PDF title page (SpringerLink, viewed November 15, 2016).

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.

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.

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