Abstract:This chapter details initially acquiring an open-source UAV dataset and creating a Google Earth dataset of vehicles, and creating the metadata for these images. Then training a deep learning object detection model, YOLOv4, to generate the best training weight files, having a very high mean average precision (mAP). It is the measure of how precisely the model is detecting the objects specified in the metadata of the validation dataset. The higher this value, the more accurate the model is, with the specific dat… Show more
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