posted by organizer: kragab || 3931 views || tracked by 4 users: [display]

Call for Book Chapter 2021 : Blockchain and Deep Learning - Future Trends and Enabling Technologies

FacebookTwitterLinkedInGoogle

Link: https://www2.cs.siu.edu/~kahmed/downloads//BookChapter_CFP_2021.pdf
 
When Feb 1, 2021 - Apr 30, 2022
Where Book Chapter
Submission Deadline Jun 14, 2021
Notification Due Aug 15, 2021
Final Version Due Sep 5, 2021
Categories    blockchain   deep learning   IOT   big data
 

Call For Papers

Call for Book Chapters

Book Title: Blockchain and Deep Learning - Future Trends and Enabling Technologies

Published by Springer, Studies in Big Data series in Year 2021

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. The main aim of this book is to identify the bedrock principles and forward projecting methodologies that illuminate the trajectory of developments for the decades ahead.
This book aims to provide a comprehensive reference for blockchain and deep learning by covering all important topics. It encourages recent studies of blockchain, deep learning and reinforcement learning with focusing on the following topics but not limited to:
Topics:
• Blockchain foundations, new design, and privacy
• Cyber-physical systems and Blockchain
• Security and data integrity with blockchain
• Cyberattacks on blockchains
• IoT platform based on Blockchain or/and deep learning
• P2P communication protocol
• Blockchain based social media
• Distributed Database Technologies for Blockchain
• Permissioned vs. permission-less paradigms
• Reinforcement learning
• Deep learning models for achieving safety
• Blockchain in connected and autonomous vehicles
• Blockchain and Machine Learning/Artificial Intelligence
• Learning at the edge of the networks
• IoT-driven intelligence and incorporate deep learning models
• Vision, Image Processing and Environment Perception
• Intelligent Automation
• Operational and Policy issues in Automation
• Big Data and Deep Learning

Submission Procedure:

All book chapters proposal must be electronically submitted by using Easychair link below, following these guidelines:

• Researchers and practitioners are kindly invited to submit chapter proposal
containing a preliminary title, a short abstract and authors affiliations.
• The length of the book chapter should be between 15 to 20 pages (including
reference).
• All submitted chapters will be reviewed by at least 2-3 reviewers on a double-
blind review basis
• Submission link:
https://easychair.org/my/conference?conf=bcdl2021

Important Dates:


June 14, 2021: Full chapter submission deadline (Extended 10 days)
August 15, 2021: Review results including notification of acceptance of chapter
Sept. 05, 2021: Final Chapter Submission (camera ready version)

Editors:

Khaled R Ahmed
School of Computing,
Southern Illinois University, USA
kahmed@cs.siu.edu

Henry Hexmoor
School of Computing,
Southern Illinois University, USA
hexmoor@cs.siu.edu


Related Resources

Call for Book Chapter 2023   Decoding Cultural Heritage: a critical dissection and taxonomy of human creativity through digital tools
IEEE Xplore-Ei/Scopus-CCCAI 2023   2023 International Conference on Communications, Computing and Artificial Intelligence (CCCAI 2023) -EI Compendex
Oikography 2023   Oikography: Homemaking through Photography
ICBDB 2023   2023 5th International Conference on Big Data and Blockchain(ICBDB 2023)
EAICI 2024   Explainable AI for Cancer Imaging
SoCAV 2024   2024 International Symposium on Connected and Autonomous Vehicles (SoCAV 2024)
blockchain_ml_iot 2023   Network (MDPI) Special Issue - Blockchain and Machine Learning for IoT: Security and Privacy Challenges
IJWesT 2023   International Journal of Web & Semantic Technology
EAIH 2024   Explainable AI for Health
IEEE Big Data - MMAI 2023   IEEE Big Data 2023 Workshop on Multimodal AI (Virtually)