Document Type : Original Article


Department of Computer Science and Technology, Henan Institute of Technology, Xinxiang 453003, China



One of the important and more challenging categories in the smart cities and IoT is to monitor the vehicles plate licenses. This system is a key factor in most of the traffic monitoring in the IoT based smart city applications. In this research, a method for plate license recognition based on optimal training of the CNN is proposed. To do this, the configuration and the hyperparameters of the CNN were optimized by a new hybrid optimization including world cup optimizer, whale optimizer, and chaotic theory to obtain a better result with high convergence. Simulations are applied to the UFPR-ALPR dataset and are compared with six popular techniques in terms of accuracy and time. Experimental achievements indicated that the proposed method gives superiority toward the other comparative techniques and is an efficient method for vehicles plate licenses detection.


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