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Multiple Classifier Systems
5th International Workshop, MCS 2004, Cagliari, Italy, June 9-11, 2004, Proceedings

Inglese · Tascabile

Spedizione di solito entro 6 a 7 settimane

Descrizione

Ulteriori informazioni

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-fertilization.

Riassunto

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-fertilization.

Dettagli sul prodotto

Con la collaborazione di Josef Kittler (Editore), Fabio Roli (Editore), Terry Windeatt (Editore), Kittler Josef (Editore)
Editore Springer, Berlin
 
Lingue Inglese
Contenuto Libro
Forma del prodotto Tascabile
Data pubblicazione 18.08.2005
Categoria Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Informatica
 
EAN 9783540221449
ISBN 978-3-540-22144-9
Numero di pagine 392
Illustrazioni XII, 392 p.
Altezza (della confezione) 23.5 cm
Peso (della confezione) 600 g
 
Serie Lecture Notes in Computer Science > 3077
Lecture Notes in Computer Science
Categorie C, Artificial Intelligence, Mustererkennung, Maschinelles Sehen, Bildverstehen, Theoretische Informatik, computer science, Neural Networks, Verification, Computer Vision, Theory of Computation, Image Processing and Computer Vision, pattern recognition, Computers, Automated Pattern Recognition, Optical data processing, Image processing, Statistical Learning, Computation by Abstract Devices, Speech recognition, multiple classifier systems
 

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