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Deep Learning on Edge Computing Devices

Author: Xichuan (Professor Zhou

SKU: 9780323857833 Category:
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Description

Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture focuses on hardware architecture and embedded deep learning, including neural networks. The title helps researchers maximize the performance of Edge-deep learning models for mobile computing and other applications by presenting neural network algorithms and hardware design optimization approaches for Edge-deep learning. Applications are introduced in each section, and a comprehensive example, smart surveillance cameras, is presented at the end of the book, integrating innovation in both algorithm and hardware architecture. Structured into three parts, the book covers core concepts, theories and algorithms and architecture optimization. This book provides a solution for researchers looking to maximize the performance of deep learning models on Edge-computing devices through algorithm-hardware co-design. show more

Additional information

Weight 328 g
Author

Xichuan (Professor Zhou

Publisher

Elsevier – Health Sciences Division

Binding

Paperback / softback

ISBN-10

0323857833

Dimensions

151 x 227 x 18

Language

English

Country of Pub

United States

Book Condition

New

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