東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Structural, syntactic, and statistic...

Robles-Kelly, Antonio.

Linked to FindBook

Google Book

Amazon

博客來

Structural, syntactic, and statistical pattern recognition = Joint IAPR International Workshop, S+SSPR 2016, Merida, Mexico, November 29 - December 2, 2016 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Structural, syntactic, and statistical pattern recognition/ edited by Antonio Robles-Kelly ... [et al.].
Reminder of title:	Joint IAPR International Workshop, S+SSPR 2016, Merida, Mexico, November 29 - December 2, 2016 : proceedings /
remainder title:	S+SSPR 2016
other author:	Robles-Kelly, Antonio.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xiii, 588 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Pattern recognition systems - Congresses. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-49055-7
ISBN:	9783319490557

Structural, syntactic, and statistical pattern recognition = Joint IAPR International Workshop, S+SSPR 2016, Merida, Mexico, November 29 - December 2, 2016 : proceedings /
Structural, syntactic, and statistical pattern recognitionJoint IAPR International Workshop, S+SSPR 2016, Merida, Mexico, November 29 - December 2, 2016 : proceedings /[electronic resource] :S+SSPR 2016edited by Antonio Robles-Kelly ... [et al.]. - Cham :Springer International Publishing :2016. - xiii, 588 p. :ill., digital ;24 cm. - Lecture notes in computer science,100290302-9743 ;. - Lecture notes in computer science ;10029..

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.

ISBN: 9783319490557

Standard No.: 10.1007/978-3-319-49055-7doiSubjects--Topical Terms:

563039
Pattern recognition systems
--Congresses.

LC Class. No.: TK7882.P3

Dewey Class. No.: 006.4

Structural, syntactic, and statistical pattern recognition = Joint IAPR International Workshop, S+SSPR 2016, Merida, Mexico, November 29 - December 2, 2016 : proceedings /
LDR:02325nmm a2200349 a 4500 001 2080619
003 DE-He213
005 20161104162505.0
006 m d
007 cr nn 008maaau
008 170616s2016 gw s 0 eng d
020 $a 9783319490557 $q (electronic bk.)
020 $a 9783319490540 $q (paper)
024 7 $a 10.1007/978-3-319-49055-7 $2 doi
035 $a 978-3-319-49055-7
040 $a GP $c GP
041 0 $a eng
050 4 $a TK7882.P3
072 7 $a UYQ $2 bicssc
072 7 $a TJFM1 $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.4 $2 23
090 $a TK7882.P3 $b S927 2016
245 0 0 $a Structural, syntactic, and statistical pattern recognition $h [electronic resource] : $b Joint IAPR International Workshop, S+SSPR 2016, Merida, Mexico, November 29 - December 2, 2016 : proceedings / $c edited by Antonio Robles-Kelly ... [et al.].
246 3 $a S+SSPR 2016
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xiii, 588 p. : $b ill., digital ; $c 24 cm.
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 Pattern recognition systems $v Congresses. $3 563039
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Pattern Recognition. $3 891045
650 2 4 $a Information Systems Applications (incl. Internet) $3 1565452
650 2 4 $a Database Management. $3 891010
650 2 4 $a Algorithm Analysis and Problem Complexity. $3 891007
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
700 1 $a Robles-Kelly, Antonio. $3 3200683
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Lecture notes in computer science ; $v 10029. $3 3200684
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-49055-7
950 $a Computer Science (Springer-11645)