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Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR & SPR 2012, Hiroshima, Japan, November 7-9, 2012, Proceedings (Paperback, 2012)
Georgy Gimel'farb, Edwin Hancock, Atsushi Imiya, Arjan Kuijper, Mineichi Kudo, …
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R1,708
Discovery Miles 17 080
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Ships in 10 - 15 working days
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This volume constitutes the refereed proceedings of the Joint IAPR
International Workshops on Structural and Syntactic Pattern
Recognition (SSPR 2012) and Statistical Techniques in Pattern
Recognition (SPR 2012), held in Hiroshima, Japan, in November 2012
as a satellite event of the 21st International Conference on
Pattern Recognition, ICPR 2012. The 80 revised full papers
presented together with 1 invited paper and the Pierre Devijver
award lecture were carefully reviewed and selected from more than
120 initial submissions. The papers are organized in topical
sections on structural, syntactical, and statistical pattern
recognition, graph and tree methods, randomized methods and image
analysis, kernel methods in structural and syntactical pattern
recognition, applications of structural and syntactical pattern
recognition, clustering, learning, kernel methods in statistical
pattern recognition, kernel methods in statistical pattern
recognition, as well as applications of structural, syntactical,
and statistical methods.
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Multiple Classifier Systems - 5th International Workshop, MCS 2004, Cagliari, Italy, June 9-11, 2004, Proceedings (Paperback, 2004 ed.)
Fabio Roli, Josef Kittler, Terry Windeatt
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R1,726
Discovery Miles 17 260
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Ships in 10 - 15 working days
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The fusion of di?erent information sourcesis a persistent and
intriguing issue. It
hasbeenaddressedforcenturiesinvariousdisciplines,
includingpoliticalscience, probability and statistics, system
reliability assessment, computer science, and distributed detection
in communications. Early seminal work on fusion was c- ried out by
pioneers such as Laplace and von Neumann. More recently, research
activities in information fusion have focused on pattern
recognition. During the 1990s, classi?erfusionschemes,
especiallyattheso-calleddecision-level, emerged under a plethora of
di?erent names in various scienti?c communities, including machine
learning, neural networks, pattern recognition, and statistics. The
d- ferent nomenclatures introduced by these communities re?ected
their di?erent perspectives and cultural backgrounds as well as the
absence of common forums and the poor dissemination of the most
important results. In 1999, the ?rst workshop on multiple classi?er
systems was organized with the main goal of creating a common
international forum to promote the diss- ination of the results
achieved in the diverse communities and the adoption of a common
terminology, thus giving the di?erent perspectives and cultural ba-
grounds some concrete added value. After ?ve meetings of this
workshop, there is strong evidence that signi?cant steps have been
made towards this goal. - searchers from these diverse communities
successfully participated in the wo- shops, and world experts
presented surveys of the state of the art from the perspectives of
their communities to aid cross-fertilizat
The refereed proceedings of the 4th International Workshop on Multiple Classifier Systems, MCS 2003, held in Guildford, UK in June 2003. The 40 revised full papers presented with one invited paper were carefully reviewed and selected for presentation. The papers are organized in topical sections on boosting, combination rules, multi-class methods, fusion schemes and architectures, neural network ensembles, ensemble strategies, and applications
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