The incorporation of deep-learning techniques in embedded systems has enhanced the
capabilities of edge computing to a great extent. However, most of these solutions rely on …

Rapid progress on disaster detection and assessment has been achieved with the
development of deep-learning techniques and the wide applications of remote sensing …

With the development of recent years, the field of deep learning has made great progress.
Compared with the traditional machine learning algorithm, deep learning can better find the …

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 …

Complex scene character recognition is a challenging yet important task in machine
learning, especially for languages with large character sets, such as Chinese, which is …

The technique of vehicle license plate recognition can recognize and count the vehicles
automatically, and thus many applications regarding the vehicles are greatly facilitated …

In this study, the authors are interested in building a unified deep learning framework to
solve the recognition problem of both single‐line and double‐line car license plates. Most …

The license plate recognition is an important part of the intelligent traffic management
system, and the application of deep learning to the license plate recognition system can …

This paper proposed LONTAR_DETC, a method to detect handwritten Balinese characters
in Lontar manuscripts. LONTAR_DETC is a deep learning architecture based on YOLO. The …

Variable-length license plate segmentation and recognition has always been a challenging
barrier in the application of intelligent transportation systems. Previous approaches mainly …