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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Lingua: Inglese
Editore: Springer-Verlag New York Inc, 2013
ISBN 10: 3642391397 ISBN 13: 9783642391392
Da: Revaluation Books, Exeter, Regno Unito
EUR 79,55
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Aggiungi al carrelloPaperback. Condizione: Brand New. 2013 edition. 307 pages. 8.43x5.85x0.73 inches. In Stock.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 53,49
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of the Second International Workshop on Similarity Based Pattern Analysis and Recognition, SIMBAD 2013, which was held in York, UK, in July 2013.The 18 papers presented were carefully reviewed and selected from 33 submissions. They cover a wide range of problems and perspectives, from supervised to unsupervised learning, from generative to discriminative models, from theoretical issues to real-world practical applications, and offer a timely picture of the state of the art in the field.
Da: preigu, Osnabrück, Germania
EUR 50,35
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Similarity-Based Pattern Recognition | Second International Workshop, SIMBAD 2013, York, UK, July 3-5, 2013, Proceedings | Edwin Hancock (u. a.) | Taschenbuch | x | Englisch | 2013 | Springer | EAN 9783642391392 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 109,17
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Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 99,69
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Aggiungi al carrelloPaperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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EUR 130,22
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Da: Buchpark, Trebbin, Germania
EUR 40,42
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Aggiungi al carrelloCondizione: Sehr gut. Zustand: Sehr gut | Seiten: 308 | Sprache: Englisch | Produktart: Bücher | This book constitutes the proceedings of the Second International Workshop on Similarity Based Pattern Analysis and Recognition, SIMBAD 2013, which was held in York, UK, in July 2013. The 18 papers presented were carefully reviewed and selected from 33 submissions. They cover a wide range of problems and perspectives, from supervised to unsupervised learning, from generative to discriminative models, from theoretical issues to real-world practical applications, and offer a timely picture of the state of the art in the field.