Edité par Berlin, Springer, 2008
Langue: anglais
Vendeur : Antiquariat Thomas Haker GmbH & Co. KG, Berlin, Allemagne
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Ajouter au panierHardcover. Etat : Wie neu. 248 S.; Ill. Like new. Shrink wrapped. Sprache: Englisch Gewicht in Gramm: 735.
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Ajouter au panierEtat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher.
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Ajouter au panierRustica (tapa blanda). Etat : New. Etat de la jaquette : Nuevo. 1. LIBRO.
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EUR 64,20
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Edité par Springer London, Springer London, 2016
ISBN 10 : 1447171330 ISBN 13 : 9781447171331
Langue: anglais
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 64,39
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Ajouter au panierTaschenbuch. Etat : 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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Ajouter au panierBrand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Ajouter au panierEtat : New. pp. 276.
Vendeur : Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlande
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Ajouter au panierEtat : New. 2016. Paperback. . . . . .
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Edité par Springer-Verlag New York Inc, 2016
ISBN 10 : 1447171330 ISBN 13 : 9781447171331
Langue: anglais
Vendeur : Revaluation Books, Exeter, Royaume-Uni
EUR 91,55
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Ajouter au panierPaperback. Etat : Brand New. 2nd reprint edition. 289 pages. 9.25x6.10x0.87 inches. In Stock.
Edité par Springer London, Springer London Jan 2014, 2014
ISBN 10 : 1447163079 ISBN 13 : 9781447163077
Langue: anglais
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
EUR 85,59
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Ajouter au panierBuch. Etat : Neu. 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 292 pp. Englisch.
Edité par Springer London, Springer London, 2014
ISBN 10 : 1447163079 ISBN 13 : 9781447163077
Langue: anglais
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 90,34
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Ajouter au panierBuch. Etat : 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.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 91,11
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Ajouter au panierEtat : New.
Vendeur : Kennys Bookstore, Olney, MD, Etats-Unis
EUR 111,32
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Ajouter au panierEtat : New. 2016. Paperback. . . . . . Books ship from the US and Ireland.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 100,24
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 101,44
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
EUR 61,77
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Vendeur : Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlande
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Ajouter au panierEtat : New. Markov Models for Pattern Recognition Series: Advances in Computer Vision and Pattern Recognition. Num Pages: 276 pages, black & white illustrations. BIC Classification: UYQL; UYQP; UYT. Category: (P) Professional & Vocational. Dimension: 241 x 163 x 21. Weight in Grams: 580. . 2014. 2nd ed. 2014. Hardcover. . . . .
Edité par Springer London Ltd, England, 2016
ISBN 10 : 1447171330 ISBN 13 : 9781447171331
Langue: anglais
Vendeur : Grand Eagle Retail, Mason, OH, Etats-Unis
EUR 81,74
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Ajouter au panierPaperback. Etat : new. Paperback. 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. 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; Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
EUR 85,04
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Ajouter au panierEtat : New.
Edité par Springer London Ltd, England, 2014
ISBN 10 : 1447163079 ISBN 13 : 9781447163077
Langue: anglais
Vendeur : Grand Eagle Retail, Mason, OH, Etats-Unis
EUR 87,13
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Ajouter au panierHardcover. Etat : new. Hardcover. 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. 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; Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Vendeur : Kennys Bookstore, Olney, MD, Etats-Unis
EUR 152,80
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Ajouter au panierEtat : New. Markov Models for Pattern Recognition Series: Advances in Computer Vision and Pattern Recognition. Num Pages: 276 pages, black & white illustrations. BIC Classification: UYQL; UYQP; UYT. Category: (P) Professional & Vocational. Dimension: 241 x 163 x 21. Weight in Grams: 580. . 2014. 2nd ed. 2014. Hardcover. . . . . Books ship from the US and Ireland.
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
EUR 137,60
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Ajouter au panierHardcover. Etat : Like New. Like New. book.
Edité par Springer London Ltd, England, 2014
ISBN 10 : 1447163079 ISBN 13 : 9781447163077
Langue: anglais
Vendeur : AussieBookSeller, Truganina, VIC, Australie
EUR 164,01
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Ajouter au panierHardcover. Etat : new. Hardcover. 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. 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; Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.