9783030744809 - multi-faceted deep learning: models and data (13 risultati)

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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Lingua: Inglese
Editore: Springer, Berlin|Springer International Publishing|Springer, 2022
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Da: moluna, Greven, Germaniamoluna
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Multi-faceted Deep Learning | Models and Data | Jenny Benois-Pineau (u. a.) | Taschenbuch | xii | Englisch | 2022 | Springer | EAN 9783030744809 | 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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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

Lingua: Inglese
Editore: Springer International Publishing, Springer Nature Switzerland, 2022
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers a large set of methods in the field of Artificial Intelligence - Deep Learning applied to real-world problems.The fundamentals of the Deep Learning approach and different types of Deep Neural Networks (DNNs) are first summarized i…n this book, which offers a comprehensive preamble for further problem-oriented chapters.The most interesting and open problems of machine learning in the framework of Deep Learning are discussed in this book and solutions are proposed. This book illustrates how to implement the zero-shot learning with Deep Neural Network Classifiers, which require a large amount of training data. The lack of annotated training data naturally pushes the researchers to implement low supervision algorithms. Metric learning is a long-term research but in the framework of Deep Learning approaches, it gets freshness and originality. Fine-grained classification with a low inter-class variability is a difficult problem for any classification tasks. This book presents how it is solved, by using different modalities and attention mechanisms in 3D convolutional networks.Researchers focused on Machine Learning, Deep learning, Multimedia and Computer Vision will want to buy this book. Advanced level students studying computer science within these topic areas will also find this book useful.

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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 328 pages. 9.25x6.10x0.83 inches. In Stock.

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Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.

Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing Okt 2022, 2022
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book covers a large set of methods in the field of Artificial Intelligence - Deep Learning applied to real-world problems.The fundamentals of the Deep Learning approach and different types of Deep Neural Networks (DNNs) are fi…rst summarized in this book, which offers a comprehensive preamble for further problem-oriented chapters.The most interesting and open problems of machine learning in the framework of Deep Learning are discussed in this book and solutions are proposed. This book illustrates how to implement the zero-shot learning with Deep Neural Network Classifiers, which require a large amount of training data. The lack of annotated training data naturally pushes the researchers to implement low supervision algorithms. Metric learning is a long-term research but in the framework of Deep Learning approaches, it gets freshness and originality. Fine-grained classification with a low inter-class variability is a difficult problem for any classification tasks. This book presents how it is solved, by using different modalities and attention mechanisms in 3D convolutional networks.Researchers focused on Machine Learning, Deep learning, Multimedia and Computer Vision will want to buy this book. Advanced level students studying computer science within these topic areas will also find this book useful. 328 pp. Englisch.

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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 192,59
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book covers a large set of methods in the field of Artificial Intelligence - Deep Learning applied to real-world problems. The fundamentals of the Deep Learning approach and different types of Deep Neural Networks (DNNs) are first… summarized in this book, which offers a comprehensive preamble for further problem-oriented chapters.The most interesting and open problems of machine learning in the framework of Deep Learning are discussed in this book and solutions are proposed. This book illustrates how to implement the zero-shot learning with Deep Neural Network Classifiers, which require a large amount of training data. The lack of annotated training data naturally pushes the researchers to implement low supervision algorithms. Metric learning is a long-term research but in the framework of Deep Learning approaches, it gets freshness and originality. Fine-grained classification with a low inter-class variability is a difficult problem for any classification tasks. This book presents how it is solved, by using different modalities and attention mechanisms in 3D convolutional networks.Researchers focused on Machine Learning, Deep learning, Multimedia and Computer Vision will want to buy this book. Advanced level students studying computer science within these topic areas will also find this book useful.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 328 pp. Englisch.

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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND.