Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques
Seiten
2022
Business Science Reference (Verlag)
978-1-7998-8763-8 (ISBN)
Business Science Reference (Verlag)
978-1-7998-8763-8 (ISBN)
Explores artificial techniques, pattern recognition, machine and deep learning-based methods and techniques applied to different real time applications of Unmanned Aerial Vehicles (UAV). The aim is to synthesize the scope of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems and application areas.
Unmanned Aerial Vehicle (UAV) has extended the freedom to operate and monitor the activities from remote locations. It has advantages of flying at low altitude, small size, high resolution, lightweight, and portability. UAV and artificial intelligence have started gaining attentions of academic and industrial research. UAV along with machine learning has immense scope in scientific research and has resulted in fast and reliable outputs. Deep learning-based UAV has helped in real time monitoring, data collection and processing, and prediction in the computer/wireless networks, smart cities, military, agriculture and mining. This book covers artificial techniques, pattern recognition, machine and deep learning – based methods and techniques applied to different real time applications of UAV. The main aim is to synthesize the scope and importance of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems and numerous application areas.
This book is ideal for researchers, scientists, engineers and designers in academia and industry working in the fields of computer science, computer vision, pattern recognition, machine learning, imaging, feature engineering, UAV and sensing.
Unmanned Aerial Vehicle (UAV) has extended the freedom to operate and monitor the activities from remote locations. It has advantages of flying at low altitude, small size, high resolution, lightweight, and portability. UAV and artificial intelligence have started gaining attentions of academic and industrial research. UAV along with machine learning has immense scope in scientific research and has resulted in fast and reliable outputs. Deep learning-based UAV has helped in real time monitoring, data collection and processing, and prediction in the computer/wireless networks, smart cities, military, agriculture and mining. This book covers artificial techniques, pattern recognition, machine and deep learning – based methods and techniques applied to different real time applications of UAV. The main aim is to synthesize the scope and importance of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems and numerous application areas.
This book is ideal for researchers, scientists, engineers and designers in academia and industry working in the fields of computer science, computer vision, pattern recognition, machine learning, imaging, feature engineering, UAV and sensing.
Bella Mary I. Thusnavis, Karunya Institute of Technology and Sciences, India K. Martin Sagayam, Karunya Institute of Technology and Sciences, India Ahmed A. Elngar, Faculty of Computers & Artificial Intelligence Beni-Suef University, Beni Suef City, Egypt
| Erscheinungsdatum | 01.12.2021 |
|---|---|
| Sprache | englisch |
| Maße | 216 x 279 mm |
| Gewicht | 363 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Fahrzeugbau / Schiffbau | |
| Technik ► Luft- / Raumfahrttechnik | |
| ISBN-10 | 1-7998-8763-4 / 1799887634 |
| ISBN-13 | 978-1-7998-8763-8 / 9781799887638 |
| Zustand | Neuware |
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