Artificial Neural Networks in Pattern Recognition : Third Iapr Tc3 Workshop, Annpr 2008 Paris, France, July 2-4, 2008, Proceedings (Lecture Notes in C

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Artificial Neural Networks in Pattern Recognition : Third Iapr Tc3 Workshop, Annpr 2008 Paris, France, July 2-4, 2008, Proceedings (Lecture Notes in C

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 318 p.
  • 言語 ENG
  • 商品コード 9783540699385
  • DDC分類 006

Full Description

TheThirdIAPRTC3WorkshoponArti?cialNeuralNetworksinPatternRec- nition, ANNPR 2008, was held at Pierre and Marie Curie University in Paris (France), July 2-4, 2008. The workshop was organized by the Technical C- mittee on Neural Networks and Computational Intelligence (TC3) that is one of the 20 TCs of the International Association for Pattern Recognition (IAPR). The scope of TC3 includes computational intelligence approaches, such as fuzzy systems, evolutionary computing and arti?cial neural networks and their use in various pattern recognition applications. ANNPR 2008 followed the success of the previous workshops: ANNPR 2003 held at the University of Florence (Italy) andANPPR 2006held at ReisensburgCastle, Universityof Ulm (Germany).All the workshops featured a single-track program including both oral sessions and posters with a focus on active participation from every participant. Inrecentyears,the?eld ofneuralnetworkshasmaturedconsiderablyinboth methodologyandreal-worldapplications.Asre?ectedinthisbook,arti?cialn- ral networks in pattern recognition combine many ideas from machine learning, advanced statistics, signal and image processing for solving complex real-world pattern recognition problems.
High quality across such a diverse ?eld of research can only be achieved through a rigorous and selective review process. For this workshop, 57 papers were submitted out of which 29 were selected for inclusion in the proceedings. The oral sessions included 18 papers, while 11 contributions were presented as posters. ANNPR 2008 featured research works in the areas of supervised and unsupervised learning, multiple classi?er systems, pattern recognition in signal and image processing, and feature selection.

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