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9781447171331 - Markov Models for Pattern Recognition: from Theory to Applications Advances in Computer Vision and Pattern Recognition by Fink, Gernot a (18 results)
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Rustica (tapa blanda). Condition: New. Dust Jacket Condition: Nuevo. 1. LIBRO.
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Condition: As New. Unread book in perfect condition.
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Markov Models for Pattern Recognition: From Theory to Applications (Advances in Computer Vision and Pattern Recognition)
Book 38 of 86: Advances in Computer Vision and Pattern RecognitionSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 55.51
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Markov Models for Pattern Recognition : From Theory to Applications
Book 38 of 86: Advances in Computer Vision and Pattern RecognitionSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Markov Models for Pattern Recognition : From Theory to Applications
Book 38 of 86: Advances in Computer Vision and Pattern RecognitionSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Markov Models for Pattern Recognition: From Theory to Applications
Book 38 of 86: Advances in Computer Vision and Pattern RecognitionLanguage: English
Published by Springer-Verlag New York Inc, 2016
ISBN 10: 1447171330 ISBN 13: 9781447171331
Paperback. Condition: Brand New. 2nd reprint edition. 289 pages. 9.25x6.10x0.87 inches. In Stock.
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Markov Models for Pattern Recognition : From Theory to Applications
Book 38 of 86: Advances in Computer Vision and Pattern RecognitionLanguage: English
Published by Springer London, Springer, 2016
ISBN 10: 1447171330 ISBN 13: 9781447171331
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n -best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.
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Taschenbuch. Condition: Neu. Markov Models for Pattern Recognition | From Theory to Applications | Gernot A. Fink | Taschenbuch | Advances in Computer Vision and Pattern Recognition | xiii | Englisch | 2016 | Springer | EAN 9781447171331 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Condition: new. Questo è un articolo print on demand.
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Markov Models for Pattern Recognition
Book 38 of 86: Advances in Computer Vision and Pattern RecognitionLanguage: English
Published by Springer London Aug 2016, 2016
ISBN 10: 1447171330 ISBN 13: 9781447171331
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n -best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models. 292 pp. Englisch.
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Markov Models for Pattern Recognition: From Theory to Applications
Book 38 of 86: Advances in Computer Vision and Pattern RecognitionSeller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 64.85
£ 15.25 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Thoroughly revised, updated and expanded new editionExamines pattern recognition systems from the perspective of Markov models, demonstrating how the models can be used in a range of applicationsPlaces special emphasis on practical algorith.
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Markov Models for Pattern Recognition
Book 38 of 86: Advances in Computer Vision and Pattern RecognitionLanguage: English
Published by Springer, Springer Aug 2016, 2016
ISBN 10: 1447171330 ISBN 13: 9781447171331
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 292 pp. Englisch.
