Deep Learning-Powered Technologies

Autonomous Driving, Artificial Intelligence of Things (AIoT), Augmented Reality, 5G Communications and Beyond

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Verlag: Springer Nature Switzerland

ISBN: 978-3-031-35739-8

GTIN: 9783031357398

Einband: Kartonierter Einband (Kt)

Verfügbarkeit: Folgt in ca. 5 Arbeitstagen

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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

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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

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Autor	Mohamed, Khaled Salah
Verlag	Springer Nature Switzerland
Einband	Kartonierter Einband (Kt)
Erscheinungsjahr	2024
Seitenangabe	224 S.
Ausgabekennzeichen	Englisch
Masse	H24.0 cm x B16.8 cm x D1.3 cm 384 g
Auflage	2023
Gewicht	384
ISBN	978-3-031-35739-8

Über den Autor Khaled Salah Mohamed

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 Masters 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.