Advances in both parallel processing capabilities because of graphical processing units
(GPUs) and computer vision algorithms have led to the development of deep neural …

Traffic load is a crucial but complicated factor in determining the in-service performance and
deterioration behavior of bridges. A better understanding of traffic loads in different traffic …

Automatic License Plate Recognition (ALPR) systems have shown remarkable performance
on license plates (LPs) from multiple regions due to advances in deep learning and the …

License plate recognition (LPR) is an integral part of the current intelligent systems that are
developed to locate and identify various objects. Unfortunately, the LPR is a challenging …

Recently, with the development of deep learning, Automatic License Plate Recognition
(ALPR) has made great progress, However, there are still many challenges to accomplish …

In the past few decades, license plate detection and recognition (LPDR) systems have made
great strides relying on Convolutional Neural Networks (CNN). However, these methods are …

Recent years have seen significant developments in the field of License Plate Recognition
(LPR) through the integration of deep learning techniques and the increasing availability of …

This work draws attention to the large fraction of near-duplicates in the training and test sets
of datasets widely adopted in License Plate Recognition (LPR) research. These duplicates …

Abstract Automatic Number Plate Recognition System provides a solution for traffic jam in
Toll Tax, used by Traffic police and also for security purpose. The main purpose of Automatic …

Public datasets have played a key role in advancing the state of the art in License Plate
Recognition (LPR). Although dataset bias has been recognized as a severe problem in the …