“…Many color-based methods (Shi et al, 2005;Chen et al, 2009) usually use the combination of the license plate and the characters. However, since the two-stage methods are not only slow to run, but also take more time to converge for optimized training due to the double networks, one-stage pipeline based methods, segmentation-free approach (Zherzdev and Gruzdev, 2018;Cheang et al, 2017;Li and Shen, 2016;, including segmentation and recognition at once, are proposed. Most segmentation-free models take advantage of deeply learned features which outperforms traditional methods on the task of classification by deep convolutional neural networks (DCNN) (Simonyan and Zisserman, 2014;He et al, 2016) and data-driven approaches (Russakovsky et al, 2015).…”