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Multi Faceted Deep Learning Models (21 results)
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Multi-faceted Deep Learning: Models and Data
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Multi-faceted Deep Learning: Models and Data
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 203.56
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Multi-faceted Deep Learning : Models and Data
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Multi-faceted Deep Learning : Models and Data
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Taschenbuch. Condition: 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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Multi-faceted Deep Learning : Models And
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
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Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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Multi-faceted Deep Learning : Models and Data
Language: English
Published by Springer International Publishing, Springer Nature Switzerland, 2022
ISBN 10: 3030744809 ISBN 13: 9783030744809
Taschenbuch. Condition: 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 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.
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Multi-faceted Deep Learning : Models and Data
Language: English
Published by Springer International Publishing, Springer Nature Switzerland, 2021
ISBN 10: 3030744779 ISBN 13: 9783030744779
Buch. Condition: 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 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.
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Add to basketPaperback. Condition: Brand New. 328 pages. 9.25x6.10x0.83 inches. In Stock.
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Add to basketHardcover. Condition: Brand New. 328 pages. 9.25x6.10x0.98 inches. In Stock.
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US$ 305.69
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Condition: New. PRINT ON DEMAND.
