ENGLISH

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

By Sudeep Pasricha (editor) , Muhammad Shafique (editor)

Book information

Publisher
Springer
Year
2023
ISBN
3031195671, 9783031195679
Language
english
Format
PDF
Filesize
22 MB (22873778 bytes)
Pages
426\418
Time added
2024-04-04 14:55:45

Description

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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