With the application of UAVs in intelligent transportation systems, vehicle\ndetection for aerial images has become a key engineering technology and has\nacademic research significance. In this paper, a vehicle detection method for\naerial image based on YOLO deep learning algorithm is presented. The method\nintegrates an aerial image dataset suitable for YOLO training by\nprocessing three public aerial image datasets. Experiments show that the\ntraining model has a good performance on unknown aerial images, especially\nfor small objects, rotating objects, as well as compact and dense objects, while\nmeeting the real-time requirements.
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