Category Artificial Intelligence; Convolution Neural Network; Optimization; Smart Cities; Industry 4.0

Deadline: June 21, 2021 | Date: July 21, 2121-July 22, 2121

Venue/Country: Malaysia

Updated: 2021-06-07 00:48:39 (GMT+9)

Call For Papers - CFP

Book Title: Advances of Deep Learning in Smart Cities and Industry 4.0

Publisher: Cambridge Scholars Publishing

Full Chapter Submission: 21st June, 2021

Editors

 Prof. Dr. Vasiliki Geropanta, Technical University of Crete, Greece

 Prof. Dr. Gerhard-Wilhelm Weber, Poznan University of Technology, Poland

 Dr. Joshua Thomas, UOW Malaysia; KDU Penang University College, Malaysia

 Dr. Pandian Vasant, MERLIN Research Centre, TDTU, Vietnam

ABOUT THE BOOK

Advances of Deep Learning in Smart Cities and Industry 4.0 is a collection of innovative research on the methods and applications of deep learning strategies in the fields of business, economics, finance, science and engineering. While highlighting topics including data hybridization, computational modeling, and artificial intelligence, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and policy makers seeking current research on deep learning methods and its application in the smart technology industry.

Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the fields of artificial intelligence and machine learning.

The readers across the globe are looking for wonderful material in order to provide the researchers the sufficient training of cutting-edge computation and intelligent deep learning optimization techniques to solve the complicated real world current problems. Compared with the other books, this book has a good combination of the theory introduction of advance meta-heuristics algorithm and hands-on artificial intelligence and machine learning projects. The selected demonstration problems are the hot topics in the smart cities and industry 4.0 fields. Therefore, it will become a good reference book for the young and new research scholars across the globe.

The suggested book will include the state of the art considering a number of evolutions in the domain never published before: The evolution of user-system interaction in relation to Automation, Machine Learning and Artificial Intelligence from a human perspective and the role of these technologies in the post COVID period.

Recommended topics include, but are not limited to, the following:

Machine Learning and IoT

AI simulation design for IoT devices in Smart Applications

Autonomous Systems for Industrial Informatics Applications

Computer and Machine Interface in Smart Cities Applications

Cognitive Computing and Data Analytics Techniques for Smart Cities

Deep Learning for Unstructured Data (text, images, audio, video) generated by Smart Cities Applications

New Machine Learning Algorithms for Smart Cities

IoT for City Development, intelligent districts

Intelligent Vehicles and its navigation for smart environments

Theoretical Progress of New Deep Learning Algorithms for Smart Cities

Semantic Models for Industrial Applications in Smart Cities

Target Audience

Policy makers, chief executive officers, governmental staff, academicians, research officers, post-graduates, scientist, educationist, industrialist, business leaders, entrepreneurs, engineers, city planners and decision-makers.

Submission Procedure

Authors are invited to submit the full chapter on or before 10th March 2021. Authors will be notified by 15th April 2021 about the status of their full chapters. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Advances of Deep Learning in Smart Cities and Industry 4.0. All manuscripts are accepted based on a double-blind peer review editorial process.

Guidelines for Book Chapters