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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 /

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 Techn...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Robles-Kelly, Antonio (Editor ), Loog, Marco (Editor ), Biggio, Battista (Editor ), Escolano, Francisco (Editor ), Wilson, Richard (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 10029
Temas:
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Structural, Syntactic, and Statistical Pattern Recognition  |h [electronic resource] :  |b Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings /  |c edited by Antonio Robles-Kelly, Marco Loog, Battista Biggio, Francisco Escolano, Richard Wilson. 
250 |a 1st ed. 2016. 
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300 |a XIII, 588 p. 167 illus.  |b online resource. 
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490 1 |a Image Processing, Computer Vision, Pattern Recognition, and Graphics ;  |v 10029 
505 0 |a 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. . 
520 |a 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. . 
650 0 |a Artificial intelligence. 
650 0 |a Pattern recognition systems. 
650 0 |a Application software. 
650 0 |a Database management. 
650 0 |a Algorithms. 
650 0 |a Data mining. 
650 1 4 |a Artificial Intelligence. 
650 2 4 |a Automated Pattern Recognition. 
650 2 4 |a Computer and Information Systems Applications. 
650 2 4 |a Database Management. 
650 2 4 |a Algorithms. 
650 2 4 |a Data Mining and Knowledge Discovery. 
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700 1 |a Loog, Marco.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Biggio, Battista.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Escolano, Francisco.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
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