… the detection, tracking, and geolocation of moving vehicles … real-time framework for automated
vehicle detection, tracking, and geolocation in UAV-acquired images which enlist detection…

… , real-time framework for automated vehicle detection, tracking, and geolocation in UAV-acquired
images which enlist detection, location, and tracking features to improve the final …

… Existing vehicle detection approaches can be roughly divided into traditional and deep
learning-based vehicle detection algorithms. Traditional vehicle detection algorithms must extract …

… Another method, proposed in [11], is FRCNN-based reinforcement learning for real-time
vehicle recognition, tracking, and geolocation using UAS. Tiny object sizes and complicated …

… machine learning technologies using compact neural processing units (NPUs) on board small
UAVs to solve image recognition and object identification … the UAV position GPS data and …

… Moreover, deep learning and semantic segmentation … vehicle detection tests, so as to
further improve the real-time performance and complex scene adaptability of the target detection …

… -stage ones, excel in real-time performance but usually lag … aforementioned deep
learning-based object detection models … vehicles with similar-looking items, making vehicle …

… radars, GPS devices, can be used for traffic flow monitoring, road … Experiments in this paper
use the PyTorch deep learning … Chen, "Vehicle detection based on remote sensing image of …

… to detect similar features in overlapping images from the UAV, then uses the geolocation …
This study demonstrated the feasibility of FRCNN-based models in the prediction of potato plant …

… is to refine vehicle identification, tracking, and geolocation in UAS… reinforcement learning
based on a Fast RCNN algorithm, thus embodying the potential for precise vehicle identification…