Deep Learning-Powered Technologies - Khaled Salah Mohamed

Deep Learning-Powered Technologies

Autonomous Driving, Artificial Intelligence of Things (AIoT), Augmented Reality, 5G Communications and Beyond
Buch | Hardcover
XIII, 205 Seiten
2023 | 2023
Springer International Publishing (Verlag)
978-3-031-35736-7 (ISBN)
53,49 inkl. MwSt

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.

lt;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.

An introduction to Deep Learning.- Deep Learning for Autonomous Driving.- Deep Learning for IoT.- Deep Learning for Spatial Computing: Augmented Reality and Metaverse "The Digital Universe".- Deep Learning for 5G and Beyond.- Python for Deep Learning: A General Introduction.


Erscheinungsdatum
Reihe/Serie Synthesis Lectures on Engineering, Science, and Technology
Zusatzinfo XIII, 205 p. 165 illus., 134 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 168 x 240 mm
Gewicht 509 g
Themenwelt Mathematik / Informatik Informatik Netzwerke
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik Elektrotechnik / Energietechnik
Schlagworte AIOT • augmented reality • Autonomous Driving • Deep learning • machine learning
ISBN-10 3-031-35736-1 / 3031357361
ISBN-13 978-3-031-35736-7 / 9783031357367
Zustand Neuware
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