rewrite this paragraph On a number of open datasets including the CCPD dataset and the AOLP dataset we empirically assess the suggested strategy The intersection over Union IoU between the prediction

We conduct an empirical evaluation of the suggested approach on various open datasets such as CCPD and AOLP. The performance of the detection is measured using Intersection over Union (IoU) between the predicted and actual boxes. An underrun is defined when the IoU threshold is less than 0.5. A learning-rate of 0.01 yields accurate prediction results. To determine the end-to-end performance metric, both detection and identification are considered. The standard evaluation process is used to determine the recognition and debit outcomes. The prediction outcome is deemed accurate when the learning-rate matches the license plate identification results