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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing

Name: Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
Brand: Springer, Berlin
SKU: 9783031406799
Price: 755.15 RON
Availability: InStock

Use Cases and Emerging Challenges

Autor: Sudeep Pasricha, Muhammad Shafique

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Legare: Carte broșată

Editura: Springer, Berlin

Disponibilitate: În depozitul extern

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This book presents recent advances towards the goal of enabling efficient implementation of machine...

Informații despre carte

Autor

Sudeep Pasricha, Muhammad Shafique

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2024

Pagini

571

EAN

9783031406799

Enbook ID

46636851

Editura

Springer, Berlin

Greutate

879

Dimensiuni

155 x 235

Descriere completă

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 to demonstrate 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

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