As technology continues to develop, computer vision (CV) applications are becoming
increasingly widespread in the intelligent transportation systems (ITS) context. These …

With the rapid advancements in the field of autonomous driving, the need for faster and more
accurate object detection frameworks has become a necessity. Many recent deep learning …

Recent deep learning-based object detectors have shown compelling performance for the
detection of large objects in autonomous driving applications. However, the detection of …

Abstract Residual Network (ResNet) achieves deeper and wider networks with high-
performance gains, representing a powerful convolutional neural network architecture. In …

Road manhole covers are crucial components of urban infrastructure; however, inadequate
maintenance or poor marking can pose safety risks to vehicular traffic. This paper presents a …

In this article, we address the multi-unmanned aerial vehicle (UAV) deployment problem in
the presence of co-channel interference (CCI) for non-orthogonal multiple access (NOMA) …

Despite numerous theoretical and empirical studies exploring the spatial needs of road
users, a significant gap remains in validating these findings with extensive real-world data …

Deep learning methods, particularly in the field of vehicle detection, have significantly
increased in recent years. It plays an important role in detecting vehicles. In the case of …

The mining of open pit mines is widespread in China, and there are many cases of landslide
accidents. Therefore, the problem of slope stability is highlighted. The stability of the slope is …

Automatic traffic accidents detection has appealed to the machine vision community due to
its implications on the development of autonomous intelligent transportation systems (ITS) …