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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 / / edited by Antonio Robles-Kelly, Marco Loog, Battista Biggio, Francisco Escolano, Richard Wilson



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Titolo: Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings / / edited by Antonio Robles-Kelly, Marco Loog, Battista Biggio, Francisco Escolano, Richard Wilson Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Edizione: 1st ed. 2016.
Descrizione fisica: 1 online resource (XIII, 588 p. 167 illus.)
Disciplina: 006.4
Soggetto topico: Artificial intelligence
Pattern recognition
Application software
Database management
Algorithms
Data mining
Artificial Intelligence
Pattern Recognition
Information Systems Applications (incl. Internet)
Database Management
Algorithm Analysis and Problem Complexity
Data Mining and Knowledge Discovery
Persona (resp. second.): Robles-KellyAntonio
LoogMarco
BiggioBattista
EscolanoFrancisco
WilsonRichard
Note generali: Includes index.
Nota di contenuto: 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. .
Sommario/riassunto: 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. .
Titolo autorizzato: Structural, Syntactic, and Statistical Pattern Recognition  Visualizza cluster
ISBN: 3-319-49055-9
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910483586303321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 10029