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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Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Robles-Kelly, Antonio (Επιμελητής έκδοσης), Loog, Marco (Επιμελητής έκδοσης), Biggio, Battista (Επιμελητής έκδοσης), Escolano, Francisco (Επιμελητής έκδοσης), Wilson, Richard (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
Σειρά:Lecture Notes in Computer Science, 10029
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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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. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2016. 
300 |a XIII, 588 p. 167 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
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490 1 |a Lecture Notes in Computer Science,  |x 0302-9743 ;  |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 Computer science. 
650 0 |a Algorithms. 
650 0 |a Database management. 
650 0 |a Data mining. 
650 0 |a Artificial intelligence. 
650 0 |a Pattern recognition. 
650 1 4 |a Computer Science. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Pattern Recognition. 
650 2 4 |a Information Systems Applications (incl. Internet). 
650 2 4 |a Database Management. 
650 2 4 |a Algorithm Analysis and Problem Complexity. 
650 2 4 |a Data Mining and Knowledge Discovery. 
700 1 |a Robles-Kelly, Antonio.  |e editor. 
700 1 |a Loog, Marco.  |e editor. 
700 1 |a Biggio, Battista.  |e editor. 
700 1 |a Escolano, Francisco.  |e editor. 
700 1 |a Wilson, Richard.  |e editor. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783319490540 
830 0 |a Lecture Notes in Computer Science,  |x 0302-9743 ;  |v 10029 
856 4 0 |u http://dx.doi.org/10.1007/978-3-319-49055-7  |z Full Text via HEAL-Link 
912 |a ZDB-2-SCS 
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950 |a Computer Science (Springer-11645)