Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture


Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture
Author: Xichuan Zhou ,Haijun Liu,Cong Shi,Ji Liu(Author)
Publisher finelybook 出版社: Elsevier; (February 21, 2022)
Language 语言: English
Print Length 页数: 198 pages
ISBN-10: 0323857833
ISBN-13: 9780323857833


Book Description
By finelybook

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 Author: 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.

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