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