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US$ 67.00
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Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS) (Spanish Edition)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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US$ 74.08
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing : Hardware Architectures
Published by Springer International Publishing, 2023
ISBN 10: 3031195671 ISBN 13: 9783031195679
Language: English
US$ 88.61
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Add to basketCondition: Hervorragend. Zustand: Hervorragend | Seiten: 428 | Sprache: Englisch | Produktart: Bücher.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing : Hardware Architectures
Published by Springer International Publishing, Springer International Publishing, 2024
ISBN 10: 3031195701 ISBN 13: 9783031195709
Language: English
US$ 108.21
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Add to basketTaschenbuch. Condition: 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.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Hardware Architectures
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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US$ 150.96
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
Published by Springer International Publishing, Springer Nature Switzerland Okt 2024, 2024
ISBN 10: 3031195701 ISBN 13: 9783031195709
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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US$ 108.21
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Add to basketTaschenbuch. Condition: 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 428 pp. Englisch.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing : Hardware Architectures
Published by Springer International Publishing, Springer Nature Switzerland, 2023
ISBN 10: 3031195671 ISBN 13: 9783031195679
Language: English
US$ 152.77
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Add to basketBuch. Condition: 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.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing : Software Optimizations and Hardware/Software Codesign
Published by Springer Nature Switzerland, Springer Nature Switzerland, 2024
ISBN 10: 303139934X ISBN 13: 9783031399343
Language: English
US$ 178.24
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Add to basketTaschenbuch. Condition: 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.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing : Use Cases and Emerging Challenges
Published by Springer Nature Switzerland, Springer Nature Switzerland, 2024
ISBN 10: 3031406796 ISBN 13: 9783031406799
Language: English
US$ 178.24
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Add to basketTaschenbuch. Condition: 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 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.
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US$ 202.66
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
Published by Springer International Publishing, Springer Nature Switzerland Okt 2023, 2023
ISBN 10: 3031195671 ISBN 13: 9783031195679
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
US$ 152.77
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Add to basketBuch. Condition: 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 428 pp. Englisch.
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US$ 212.39
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Add to basketHardcover. Condition: Brand New. 426 pages. 9.25x6.10x9.21 inches. In Stock.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
Published by Springer Nature Switzerland, Springer Nature Switzerland Okt 2024, 2024
ISBN 10: 303139934X ISBN 13: 9783031399343
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
US$ 178.24
Convert currencyUS$ 63.54 shipping from Germany to U.S.A.Quantity: 2 available
Add to basketTaschenbuch. Condition: 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.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
Published by Springer Nature Switzerland, Springer Nature Switzerland Okt 2024, 2024
ISBN 10: 3031406796 ISBN 13: 9783031406799
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
US$ 178.24
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Add to basketTaschenbuch. Condition: 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 588 pp. Englisch.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Software Optimizations and Hardware/Software Codesign
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 238.16
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Use Cases and Emerging Challenges
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 238.16
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Condition: New.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing : Software Optimizations and Hardware/Software Codesign
Published by Springer Nature Switzerland, Springer International Publishing, 2023
ISBN 10: 3031399315 ISBN 13: 9783031399312
Language: English
US$ 254.63
Convert currencyUS$ 37.52 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketBuch. Condition: 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.
