中华商务全球图书采选平台SinoVIP Global Book Services
在线询价Online Enquiry
订单跟踪Order Tracking
登录Sign In
/
注册Sign Up
我的单据My Lists
帮助中心Help & Services
首页/Home>书目采选/Bibliographic selection>书籍详情/Book Detail:Deep Learning-Powered Technologies: Autonomous Driving, Artificial Intelligence of Things (Aiot), Augmented Reality, 5g Communications and Beyond>
Deep Learning-Powered Technologies: Autonomous Driving, Artificial Intelligence of Things (Aiot), Augmented Reality, 5g Communications and Beyond
Mohamed, Khaled Salah

Deep Learning-Powered Technologies: Autonomous Driving, Artificial Intelligence of Things (Aiot), Augmented Reality, 5g Communications and Beyond

深度学习驱动技术:自动驾驶、物联网(Aiot)、增强现实、5g通信等

ISBN
9783031357367
作者Author
Mohamed, Khaled Salah
出版社Publisher
Springer
出版时间Published
2023-06
产品分类SIC
01020K0501-微电子学与电信技术
装帧Format
精装
语种Language
英文
页数Page
216
数量Qty
编辑推荐 | Editors' Choice

This book covers various, leading-edge deep learning technologies. The author discusses new applications of deep learning and gives insight into the integration of deep learning with various application domains, such as autonomous driving, augmented reality, AIOT, 5G and beyond.

前言 | Preface

<p>Khaled Salah Mohamed attended the school of engineering, Department of Electronics and Communications at Ain-Shams University from 1998 to 2003, where he received his B.Sc. degree in Electronics and Communications Engineering with distinction and honors. He received his Master's degree in Electronics from Cairo University, Egypt in 2008. He received his PhD degree in 2012. Dr. Khaled Salah is currently an Applications Engineering Consultant for Siemens Digital Industries Software, in Freemont, CA. Dr. Khaled Salah has published a large number of papers in in the top refereed journals and conferences. His research interests are in 3D integration, IP Modeling, and SoC design.</p>

产品详情 | Detail
This book covers various, leading-edge deep learning technologies. The author discusses new applications of deep learning and gives insight into the integration of deep learning with various application domains, such as autonomous driving, augmented reality, AIOT, 5G and beyond.
In addition, this book:
  • Discusses fundamental techniques and tools for deep learning, including a deep dive into the Python language
  • Explores the state-of-the-art applications of machine and deep learning
  • Includes a comparative study of different deep learning architectures, applications, tools, and platforms