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portada Embedded Machine Learning for Cyber-Physical, Iot, and Edge Computing: Hardware Architectures
Type
Physical Book
Publisher
Author
Language
English
Pages
412
Format
Hardcover
Dimensions
23.4 x 15.6 x 2.4 cm
Weight
0.77 kg.
ISBN13
9783031195679
Edition No.
1
Categories

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

Pasricha, Sudeep ; Shafique, Muhammad (Author) · Springer · Hardcover

Embedded Machine Learning for Cyber-Physical, Iot, and Edge Computing: Hardware Architectures - Pasricha, Sudeep ; Shafique, Muhammad

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Synopsis "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 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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