Embedded Deep Learning Algorithms by Moons Bert (19 results)

- Hardcover
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Condition: New. Softcover reprint of the original 1st ed. 2019 edition NO-PA16APR2015-KAP.

- Softcover
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- Hardcover
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- Softcover
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Taschenbuch. Condition: 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.

Language: English
Published by Springer International Publishing, Springer International Publishing, 2019
- Softcover
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Taschenbuch. Condition: 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 a…chieving 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.

- Hardcover
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- Softcover
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Paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Embedded Deep Learning: Algorithms, Architectures and Circuits for Always-on Neural Network Processing
Moons, Bert (Author)/ Bankman, Daniel (Author)/ Verhelst, Marian (Author)
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 224 pages. 9.25x6.10x0.67 inches. In Stock.

Language: English
Published by Springer International Publishing, Springer International Publishing, 2018
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Buch. Condition: 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 achievin…g 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.

- Hardcover
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- Softcover
- Print on Demand
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- Softcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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