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Condizione: New. Softcover reprint of the original 1st ed. 2019 edition NO-PA16APR2015-KAP.
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Embedded Deep Learning | Algorithms, Architectures and Circuits for Always-on Neural Network Processing | Bert Moons (u. a.) | Taschenbuch | xvi | Englisch | 2019 | Springer | EAN 9783030075774 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing, 2019
ISBN 10: 303007577X ISBN 13: 9783030075774
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 96,29
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers algorithmic and hardware implementation techniques to enable embedded deep learning. The authors describe synergetic design approaches on the application-, algorithmic-, computer architecture-, and circuit-level that will help in achieving the goal of reducing the computational cost of deep learning algorithms. The impact of these techniques is displayed in four silicon prototypes for embedded deep learning.Gives a wide overview of a series of effective solutions for energy-efficient neural networks on battery constrained wearable devices;Discusses the optimization of neural networks for embedded deployment on all levels of the design hierarchy - applications, algorithms, hardware architectures, and circuits - supported by real silicon prototypes;Elaborates on how to design efficient Convolutional Neural Network processors, exploiting parallelism and data-reuse, sparse operations, and low-precision computations;Supports the introduced theory and design concepts by four real silicon prototypes. The physical realization's implementation and achieved performances are discussed elaborately to illustrated and highlight the introduced cross-layer design concepts.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: Brand New. 224 pages. 9.25x6.10x0.67 inches. In Stock.
Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing, 2018
ISBN 10: 3319992228 ISBN 13: 9783319992228
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 139,09
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers algorithmic and hardware implementation techniques to enable embedded deep learning. The authors describe synergetic design approaches on the application-, algorithmic-, computer architecture-, and circuit-level that will help in achieving the goal of reducing the computational cost of deep learning algorithms. The impact of these techniques is displayed in four silicon prototypes for embedded deep learning.Gives a wide overview of a series of effective solutions for energy-efficient neural networks on battery constrained wearable devices;Discusses the optimization of neural networks for embedded deployment on all levels of the design hierarchy - applications, algorithms, hardware architectures, and circuits - supported by real silicon prototypes;Elaborates on how to design efficient Convolutional Neural Network processors, exploiting parallelism and data-reuse, sparse operations, and low-precision computations;Supports the introduced theory and design concepts by four real silicon prototypes. The physical realization's implementation and achieved performances are discussed elaborately to illustrated and highlight the introduced cross-layer design concepts.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 203,18
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Da: Biblios, Frankfurt am main, HESSE, Germania
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