Verlag: Springer Nature Switzerland, Springer Nature Switzerland Okt 2024, 2024
ISBN 10: 303139934X ISBN 13: 9783031399343
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
EUR 149,79
Währung umrechnenAnzahl: 2 verfügbar
In den WarenkorbTaschenbuch. Zustand: Neu. 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 cases 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 492 pp. Englisch.
Verlag: Springer Nature Switzerland, Springer Nature Switzerland, 2024
ISBN 10: 303139934X ISBN 13: 9783031399343
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 149,79
Währung umrechnenAnzahl: 1 verfügbar
In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 cases 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.Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing;Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization;Describes real applications todemonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.