Overview
- Provides a comprehensive reference for blockchain and deep learning by covering all important topics
- Introduces to blockchain and deep learning, explores and illustrates current and new trends that integrate them
- Is first edited focusing on merging blockchain and deep learning in cyber-physical systems and IoT platforms
Part of the book series: Studies in Big Data (SBD, volume 105)
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About this book
This book introduces to blockchain and deep learning and explores and illustrates the current and new trends that integrate them. The pace and speeds for connectivity are certain on the ascend. Blockchain and deep learning are twin technologies that are integral to integrity and relevance of network contents. Since they are data-driven technologies, rapidly growing interests exist to incorporate them in efficient and secure data sharing and analysis applications. Blockchain and deep learning are sentinel contemporary research technologies. This book provides a comprehensive reference for blockchain and deep learning by covering all important topics. It identifies the bedrock principles and forward projecting methodologies that illuminate the trajectory of developments for the decades ahead.
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Keywords
Table of contents (15 chapters)
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Enabling Technologies
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Applications
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Emerging Technologies
Editors and Affiliations
Bibliographic Information
Book Title: Blockchain and Deep Learning
Book Subtitle: Future Trends and Enabling Technologies
Editors: Khaled R. Ahmed, Henry Hexmoor
Series Title: Studies in Big Data
DOI: https://doi.org/10.1007/978-3-030-95419-2
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-95418-5Published: 29 March 2022
Softcover ISBN: 978-3-030-95421-5Published: 30 March 2023
eBook ISBN: 978-3-030-95419-2Published: 25 March 2022
Series ISSN: 2197-6503
Series E-ISSN: 2197-6511
Edition Number: 1
Number of Pages: X, 349
Number of Illustrations: 34 b/w illustrations, 122 illustrations in colour
Topics: Data Engineering, Cyber-physical systems, IoT, Computational Intelligence, Big Data