TY  - BOOK
AU  - Robles-Kelly,Antonio A.
AU  - Loog,Marco
AU  - Biggio,Battista
AU  - Escolano,Francisco
AU  - Wilson,Richard
ED  - International Workshop on Structural and Syntactic Pattern Recognition
ED  - International Workshop on Statistical Techniques in Pattern Recognition
TI  - Structural, syntactic, and statistical pattern recognition: joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29-December 2, 2016, Proceedings 
T2  - Lecture notes in computer science,
SN  - 9783319490557
AV  - TK7882.P3 
U1  - 006.4 23
PY  - 2016///
CY  - Cham, Switzerland
PB  - Springer
KW  - Pattern recognition systems
KW  - Congresses
KW  - Reconnaissance des formes (Informatique)
KW  - Congrès
KW  - Pattern recognition
KW  - bicssc
KW  - Information retrieval
KW  - Databases
KW  - Algorithms & data structures
KW  - Data mining
KW  - Artificial intelligence
KW  - Computers
KW  - Computer Vision & Pattern Recognition
KW  - bisacsh
KW  - Information Technology
KW  - Database Management
KW  - General
KW  - Programming
KW  - Algorithms
KW  - Data Mining
KW  - Intelligence (AI) & Semantics
KW  - fast
KW  - Congress
KW  - proceedings (reports)
KW  - aat
KW  - Conference papers and proceedings
KW  - lcgft
KW  - Actes de congrès
KW  - rvmgf
N1  - International conference proceedings; Includes author index; 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
N2  - 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
UR  - https://link.springer.com/10.1007/978-3-319-49055-7
ER  -