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Structural Syntactic And Statistical Pattern Recognition Joint Iapr International Workshop Sspr Spr 2008 Orlando Usa December 46 2008 Proceedings 1st Edition Tin Kam Ho Auth

  • SKU: BELL-2040114
Structural Syntactic And Statistical Pattern Recognition Joint Iapr International Workshop Sspr Spr 2008 Orlando Usa December 46 2008 Proceedings 1st Edition Tin Kam Ho Auth
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Structural Syntactic And Statistical Pattern Recognition Joint Iapr International Workshop Sspr Spr 2008 Orlando Usa December 46 2008 Proceedings 1st Edition Tin Kam Ho Auth instant download after payment.

Publisher: Springer-Verlag Berlin Heidelberg
File Extension: PDF
File size: 39.56 MB
Pages: 1011
Author: Tin Kam Ho (auth.), Niels da Vitoria Lobo, Takis Kasparis, Fabio Roli, James T. Kwok, Michael Georgiopoulos, Georgios C. Anagnostopoulos, Marco Loog (eds.)
ISBN: 9783540896883, 3540896880
Language: English
Year: 2008
Edition: 1

Product desciption

Structural Syntactic And Statistical Pattern Recognition Joint Iapr International Workshop Sspr Spr 2008 Orlando Usa December 46 2008 Proceedings 1st Edition Tin Kam Ho Auth by Tin Kam Ho (auth.), Niels Da Vitoria Lobo, Takis Kasparis, Fabio Roli, James T. Kwok, Michael Georgiopoulos, Georgios C. Anagnostopoulos, Marco Loog (eds.) 9783540896883, 3540896880 instant download after payment.

This book constitutes the refereed proceedings of the 12th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2008 and the 7th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2008, held jointly in Orlando, FL, USA, in December 2008 as a satellite event of the 19th International Conference of Pattern Recognition, ICPR 2008.

The 56 revised full papers and 42 revised poster papers presented together with the abstracts of 4 invited papers were carefully reviewed and selected from 175 submissions. The papers are organized in topical sections on graph-based methods, probabilistic and stochastic structural models for PR, image and video analysis, shape analysis, kernel methods, recognition and classification, applications, ensemble methods, feature selection, density estimation and clustering, computer vision and biometrics, pattern recognition and applications, pattern recognition, as well as feature selection and clustering.

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