9783031406768 - embedded machine learning for cyber-physical, iot, and edge computing: use cases and emerging challenges (9 risultati)

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Da: Basi6 International, Irving, TX, U.S.A.Basi6 International
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Condizione: Brand New. New. Delivery takes 25-30 days. Excellent Customer Service.

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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New. pp. 588 1st ed. 2024 edition NO-PA16APR2015-KAP.

Lingua: Inglese
Editore: Springer Nature Switzerland, Springer Nature Switzerland, 2023
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 213,99
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents recent advances towards thegoal ofenabling efficient implementation ofmachine learning models onresource-constrained systems, covering different application domains. Thefocus is onpresenting interesting and new use cases ofapplying mac…hine learning toinnovative application domains, exploring theefficient hardware design ofefficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques forenergy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques forachieving even greater energy, reliability, and performance benefits.Discusses efficient implementation ofmachine learning in embedded, CPS, IoT, and edge computing;Offers comprehensive coverage ofhardware design, software design, and hardware/software co-design and co-optimization;Describes real applications todemonstrate how embedded, CPS, IoT, and edge applications benefit frommachine learning.

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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Hardcover. Condizione: Brand New. 586 pages. 9.25x6.10x9.21 inches. In Stock.

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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.

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Da: moluna, Greven, Germaniamoluna
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EUR 175,51
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discusses efficient implementation of machine learning in embedded, CPS, IoTOffers comprehensive coverage of hardware design, software designDescribes real applications to demonstrate how embedded, CPS, IoT…Sudeep Pasricha is a Wa.

Lingua: Inglese
Editore: Springer Nature Switzerland, Springer Nature Switzerland Okt 2023, 2023
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 213,99
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents recent advances towards thegoal ofenabling efficient implementation ofmachine learning models onresource-constrained systems, covering different application domains. Thefocus is onpresenting interesting and new use case…s ofapplying machine learning toinnovative application domains, exploring theefficient hardware design ofefficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques forenergy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques forachieving even greater energy, reliability, and performance benefits.Discusses efficient implementation ofmachine learning in embedded, CPS, IoT, and edge computing;Offers comprehensive coverage ofhardware design, software design, and hardware/software co-design and co-optimization;Describes real applications todemonstrate how embedded, CPS, IoT, and edge applications benefit frommachine learning. 588 pp. Englisch.

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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 213,99
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use ca…ses of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 588 pp. Englisch.