Название: Deep Learning for Unmanned Systems
Автор: Anis Koubaa, Ahmad Taher Azar
Издательство: Springer
Год: 2021
Страниц: 731
Язык: английский
Формат: pdf (true)
Размер: 21.4 MB

This book is used at the graduate or advanced undergraduate level and many others. Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future. These applications include, but are not limited to, surveillance, search and rescue, environment monitoring, infrastructure monitoring, self-driving cars, contactless last-mile delivery vehicles, autonomous ships, precision agriculture and transmission line inspection to name just a few. These vehicles will benefit from advances of Deep Learning (DL) as a subfield of Machine Learning (ML) able to endow these vehicles with different capability such as perception, situation awareness, planning and intelligent control. Deep Learning models also have the ability to generate actionable insights into the complex structures of large data sets.

Deep Learning (DL) has been applied to a wide range of research areas, such as prediction, classification, image/talk recognition, and vision, and has greatly surpassed conventional methodologies. The main difference between other approaches and indepth research is the computational simulation of neural network layers by learning and multilevel representation. Therefore, the dynamic nature of large data sets can be easily understood by deep learning. Deep learning models can therefore provide insights into the complex structures of large data sets. Deep learning methods have been shown to outperform previous state-of-the-art techniques in several tasks because of the abundance of complex data from various sources (e.g., visual, audio,medical, social, and sensor).

The main reason of editing this book is the increasing demand for Deep Learning (DL), unmanned systems (USs), and the exponential growth and evolution of USs in the last couple of years. This book seeks to investigate the latest Deep Learning applications in theoretical and practical fields of for any unmanned system, robot, drone, underwater, etc. The book discusses different applications of DL in drones and robotics where reinforcement learning methods have excellent potentials for use.

Both novice and expert readers should find this book a useful reference in the field of Deep Learning and reinforcement learning for unmanned systems.