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

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...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (Online service)
Outros autores: Pasricha, Sudeep (Editor), Shafique, Muhammad (Editor)
Formato: Electrónico eBook
Idioma:inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2024.
Edición:1st ed. 2024.
Subjects:
Embedded computer systems.
Cooperating objects (Computer systems).
Artificial intelligence.
Embedded Systems.
Cyber-Physical Systems.
Artificial Intelligence.
Acceso en liña:https://doi.org/10.1007/978-3-031-19568-6
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Table of Contents:
  • Introduction
  • Efficient Hardware Acceleration for Embedded Machine Learning
  • Memory Design and Optimization for Embedded Machine Learning
  • Efficient Software Design of Embedded Machine Learning
  • Hardware-Software Co-Design for Embedded Machine Learning
  • Emerging Technologies for Embedded Machine Learning
  • Mobile, IoT, and Edge Application Use-Cases for Embedded Machine Learning
  • Cyber-Physical Application Use-Cases for Embedded Machine Learning.

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