Nitin Sharma¹, Mohd Anul Haq², Pawan Kumar Dahiya³, B. R. Marwah⁴, Reema Lalit⁵, Nitin Mittal⁶, Ismail Keshta^7,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 881-895, 2023, DOI:10.32604/cmc.2023.027899

Abstract Every developing country relies on transportation, and there has been an exponential expansion in the development of various sorts of vehicles with various configurations, which is a major component strengthening the automobile sector. India is a developing country with increasing road traffic, which has resulted in challenges such as increased road accidents and traffic oversight issues. In the lack of a parametric technique for accurate vehicle recognition, which is a major worry in terms of reliability, high traffic density also leads to mayhem at checkpoints and toll plazas. A system that combines an intelligent domain approach with more sustainability indices… More >

Parneet Kaur¹, Yogesh Kumar¹, Shakeel Ahmed^2,*, Abdulaziz Alhumam², Ruchi Singla³, Muhammad Fazal Ijaz⁴

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 35-50, 2022, DOI:10.32604/cmc.2022.017681

Abstract Automatic License Plate Recognition (ALPR) systems are important in Intelligent Transportation Services (ITS) as they help ensure effective law enforcement and security. These systems play a significant role in border surveillance, ensuring safeguards, and handling vehicle-related crime. The most effective approach for implementing ALPR systems utilizes deep learning via a convolutional neural network (CNN). A CNN works on an input image by assigning significance to various features of the image and differentiating them from each other. CNNs are popular for license plate character recognition. However, little has been reported on the results of these systems with regard to unusual varieties… More >