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Añadir al carritoHardcover. Condición: Very Good. 1. Auflage. unread, some shelfwear - will be dispatched immediately.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: Books Puddle, New York, NY, Estados Unidos de America
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EUR 141,09
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: Majestic Books, Hounslow, Reino Unido
EUR 156,96
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 156,44
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Librería: Revaluation Books, Exeter, Reino Unido
EUR 196,04
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Añadir al carritoHardcover. Condición: Brand New. 224 pages. 9.25x6.10x0.67 inches. In Stock.
Idioma: Inglés
Publicado por Springer International Publishing, Springer International Publishing, 2018
ISBN 10: 3319992228 ISBN 13: 9783319992228
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 139,09
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: 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.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 203,18
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Añadir al carritoHardcover. Condición: New. New. book.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 110,26
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer International Publishing Nov 2018, 2018
ISBN 10: 3319992228 ISBN 13: 9783319992228
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 139,09
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 224 pp. Englisch.
Idioma: Inglés
Publicado por Springer International Publishing, 2018
ISBN 10: 3319992228 ISBN 13: 9783319992228
Librería: moluna, Greven, Alemania
EUR 115,65
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Gives a wide overview of a series of effective solutions for energy-efficient neural networks on battery constrained wearable devicesDiscusses the optimization of neural networks for embedded deployment on all levels of the design hierarchy.
Idioma: Inglés
Publicado por Springer, Springer Nov 2018, 2018
ISBN 10: 3319992228 ISBN 13: 9783319992228
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 139,09
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 224 pp. Englisch.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 195,93
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND.