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| Title | Unmanned Aerial Vehicle In The Machine Learning Environment |
|---|---|
| ID_Doc | 59677 |
| Authors | Khan A.I.; Al-Mulla Y. |
| Year | 2019 |
| Published | Procedia Computer Science, 160 |
| DOI | http://dx.doi.org/10.1016/j.procs.2019.09.442 |
| Abstract | The Unmanned Aerial Vehicles have extended the freedom to operate and monitor the activities from remote locations. This study retrieved and synthesized research on the use of Unmanned Aerial Vehicles along with machine learning and its algorithms in different areas and regions. The objective was to synthesize the scope and importance of machine learning models in enhancing Unmanned Aerial Vehicles capabilities, solutions to problems, and numerous application areas. The machine learning implementation has reduced numbers of challenges to Unmanned Aerial Vehicles besides enhancing the capabilities and opening the door to the different sectors. The Unmanned Aerial Vehicles and machine learning association has resulted in fast and reliable outputs. The combination of Unmanned Aerial Vehicles and machine learning helped in real time monitoring, data collection and processing, and prediction in the computer/wireless networks, smart cities, military, agriculture, and mining. © 2019 The Authors. Published by Elsevier B.V. |
| Author Keywords | Deep learning; Drone; Machine learning; Neural network; Object detection; Pattern recognition; Unmanned aerial vehicle |
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