Description: Deep Learning on Edge Computing Devices : Design Challenges of Algorithm and Architecture, Paperback by Zhou, Xichuan; Liu, Haijun; Liu, Ji; Shi, Cong, ISBN 0323857833, ISBN-13 9780323857833, Like New Used, Free shipping in the US 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 th, integrating innovation in both algorithm and hardware architecture. Structured into three parts, th 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.
- Focuses on hardware architecture and embedded deep learning, including neural networks
- Brings together neural network algorithm and hardware design optimization approaches to deep learning, alongside real-world applications
- Considers how Edge computing solves privacy, latency and power consumption concerns related to the use of the Cloud
- Describes how to maximize the performance of deep learning on Edge-computing devices
- Presents the latest research on neural network compression coding, deep learning algorithms, chip co-design and intelligent monitoring
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Book Title: Deep Learning on Edge Computing Devices : Design Challenges of Al
Number of Pages: 210 Pages
Language: English
Publication Name: Deep Learning on Edge Computing Devices : Design Challenges of Algorithm and Architecture
Publisher: Elsevier
Publication Year: 2022
Subject: Intelligence (Ai) & Semantics, General
Type: Textbook
Item Length: 9 in
Subject Area: Computers, Science
Author: Haijun Liu, Xichuan Zhou, Ji Liu, Cong Shi
Item Width: 6 in
Format: Trade Paperback
