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

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