Robotics and Internet of Things Lab

Deep Learning for Unmanned Systems


Call for Chapters


Deep learning (DL) has been applied to a wide range of research areas, such as prediction, classification, image/talk recognition, vision, etc., and has dramatically surpassed conventional methodologies. Neural networks have been the core technology that has driven the development of deep learning and artificial intelligence for around eight years from today. While deep learning is integrated into a wide range of disciplines, its usage with unmanned systems is attracting a lot of interest, considering the increasing challenges to rely on deep learning approaches for autonomous unmanned systems. Self-driving cars represent the most important application of deep learning for autonomous unmanned systems. Besides, unmanned aerial systems and ground robots have leveraged deep neural networks to improve their perception capability and understanding of their surroundings. Although there has been dramatically advanced with deep neural networks, there are still a lot of challenges that have to be addressed in particular for unmanned systems in terms of safety, security, reliability, accuracy, and several others. This book provides an opportunity for researchers to publish their works that address the challenges for the deployment of AI solutions for unmanned systems and also share their knowledge about the latest development of state-of-the-art deep learning approaches f unnamed systems.


The main reason for editing this book is the increasing demand for Deep learning (DL), unmanned systems (USs), and their exponential growth and evolution in the last couple of years. This book seeks to investigate the latest Deep learning applications in theoretical and practical fields for any unmanned system, self-driving cars, robots, drones, underwater, etc. The book discusses different applications of deep learning in drones where computational intelligence methods have excellent potentials for use. Both novice and expert readers should find this book a useful reference in the field of Computational Intelligence, Deep learning, and unmanned systems.


  • Anis Koubaa is a Professor in Computer Science, Director of Research and Initiatives Center, and Aide to the Rector of Research Governance in Prince Sultan University (Saudi Arabia), a Research Associate in CISTER Research Unit (Portugal). He has been leading several research projects on Deep Learning, Robotics and Internet of Things. He is the director of the Robotics and Internet of Things Unit (RIOTU) at Prince Sultan University. He is a Senior Fellow of the Higher Education Academy (SF-HEA) from the United Kingdom. Prof. Anis is the editor of several books, and author and co-author of more than 190 publications.
  • Ahmad Tahar Azar has received the M.Sc. degree in 2006 and Ph.D degree in 2009 from Faculty of Engineering, Cairo University, Egypt and he got his post- doctoral from USA. He is a research Professor at Prince Sultan University, Riyadh, Kingdom Saudi Arabia. He is also an associate professor at the Faculty of Computers and Artificial intelligence, Benha University, Egypt. Prof. Azar is the Editor in Chief of International Journal of System Dynamics Applications (IJSDA) and International Journal of Service Science, Management, Engineering, and Technology (IJSSMET) published by IGI Global, USA. Also, he is the Editor in Chief of International Journal of Intelligent Engineering Informatics (IJIEI), Inderscience Publishers, Olney, UK. Prof. Azar has worked as associate editor of IEEE Trans. Neural Networks and Learning Systems from 2013 to 2017 and Associate Editor of ISA Transactios, Elsevier from 2018 to 2020. He is currently associate editor of IEEE systems journal and Human-centric Computing and Information Sciences, Springer. Dr. Ahmad Azar has worked in the areas of Control Theory & Applications, Robotics, Process Control, Artificial Intelligence, machine learning and has authored/coauthored over 350 research publications in peer-reviewed reputed journals, book chapters and conference proceedings. He is an editor of many Books in the field of Fuzzy logic systems, modeling techniques, control systems, Robotics, computational intelligence, Chaos modeling and Machine learning published by Springer and Elsevier. Dr. Ahmad Azar is closely associated with several international journals as a reviewer. He serves as international programme committee member in many international and peer-reviewed conferences. Dr. Ahmad Azar is a senior Member of IEEE since Dec. 2013 due to his significant contributions to the profession. Dr. Ahmad Azar is the recipient of several awards including: Benha University Prize for Scientific Excellence (2015, 2016, 2017 and 2018) and Highest citation Award from Benha University (2015, 2016, 2017 and 2018). In June 2018, Prof. Azar has been awarded the Egyptian State Encouragement award in Engineering Sciences, the Academy of Scientific Research and Technology of Egypt, 2017. In July 2018 he has been selected as a member of Energy and Electricity Research council, Academy of Scientific Research, Ministry of Higher Education. In Aug. 2018 he has been selected as senior Member of International Rough Set Society (IRSS). In February 2020, Prof. Azar has been awarded the Egyptian Distinguished Order of the first class from Egyptian President. Prof. Ahmad Azar is the Chair of IEEE Computational Intelligence Society (CIS) Egypt Chapter, Vice chair of IEEE Computational Intelligence Society Interdisciplinary Emergent Technologies Task Force, vice-Chair Research Activities of IEEE Robotics and Automation Society Egypt Chapter, Committee member of IEEE CIS Task Force on Fuzzy Logic in Medical Sciences Also, he is the Vice-president (North) of System dynamics Africa Regional Chapter and an Academic Member of IEEE Systems, Man, and Cybernetics Society Technical Committee on Computational Collective Intelligence.

Publisher and Indexing

This book is expected to be published by January of 2021 by Springer. It will appear under the Studies in Computational Intelligence series. For additional information and guidelines regarding the publisher, please visit

Regarding Indexing, the book will be indexed by Scopus and will be submitted for indexing to ISI Books, and DBLP.

Due Dates

  • Abstract Due: May 30, 2020
  • Full Chapters Due: July 31, 2020
  • Chapter Acceptance Notification: October 31, 2020
  • Revised Version Due Date: November 30, 2020
  • Revised Chapter Acceptance Notification: December 15, 2020
  • Estimated Publication Date: January 2021

Topics of Interest

Any contribution that provides an added value to Robot Operating System (ROS) is of interest for the book. The topics of interest include – but not limited to- the following:
  • Self-driving cars
  • Artificial Intelligence for unmanned systems
  • Aerial image analysis using computer vision
  • Semantic segmentation
  • Generative adversarial networks
  • Computer vision based autonomous
  • Deep reinforcement learning.
  • Drones evolutionary computing
  • Unmanned Aerial systems (UAS)
  • Face recognition for unmanned systems applications
  • Natural language processing for unmanned systems applications
  • Recurrent neural networks
  • Convolutional Neural Networks
  • Performance evaluation of deep learning architectures for unmanned systems
  • AI-based autonomous systems
  • Autoencoders
  • human-robot interaction
  • Security and attacks of machine learning models
  • Deep learning-based perception
  • Computer vision
  • Anti-drone systems using AI
  • Anomaly detection
  • AI in automation
  • Smart manufacturing

Submission Procedure

Researchers and practitioners are invited to submit before June 30, 2020 a 1-3 page chapter proposal abstract clearly explaining the mission and concerns of the proposed chapter. Abstract can be submitted anytime and will be evaluated shortly to provide an early feedback to the authors. This helps as a registration of the chapter for the final submission. Submission of abstracts must be done through EasyChair system Authors of accepted proposals will be notified about the status of their proposals and sent chapter guidelines. Full chapters must be submitted by July 31, 2020 through EasyChair system. The Chapter should not exceed 50 pages with respect to Springer format. All submitted chapters will be reviewed on a single-blind review basis. Contributors may also be requested to serve as reviewers for this project.