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Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshop, SplusSSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings 1st ed. 2016 [Paperback / softback]

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  • Format: Paperback / softback, 588 pages, height x width: 235x155 mm, weight: 9007 g, 167 Illustrations, black and white; XIII, 588 p. 167 illus., 1 Paperback / softback
  • Series: Lecture Notes in Computer Science 10029
  • Pub. Date: 05-Nov-2016
  • Publisher: Springer International Publishing AG
  • ISBN-10: 3319490540
  • ISBN-13: 9783319490540
  • Paperback / softback
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  • Format: Paperback / softback, 588 pages, height x width: 235x155 mm, weight: 9007 g, 167 Illustrations, black and white; XIII, 588 p. 167 illus., 1 Paperback / softback
  • Series: Lecture Notes in Computer Science 10029
  • Pub. Date: 05-Nov-2016
  • Publisher: Springer International Publishing AG
  • ISBN-10: 3319490540
  • ISBN-13: 9783319490540

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. 

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.