Artificial Intelligence has been widely applied in intelligent transportation systems. In this
work, Swin-APT, a deep learning-based approach for semantic segmentation and object …

Hazardous material vehicles are a non-negligible mobile source of danger in transport and
pose a significant safety risk. At present, the current detection technology is well developed …

Recently, the rapid development of convolutional neural networks (CNN) has consistently
improved object detection performance using CNN and has naturally been implemented in …

Object recognition algorithms such as the YOLOv3 algorithm have a lot of possible
applications in the field of medicine. One such application is the study's aim of recognizing …

Vehicular detection is an important research area in the field of target detection. The
implementation of accurate vehicle recognition models for both day and night conditions will …

Human detection within the operating area of electromechanical equipment is essential to
ensure safe production and avoid accidents in the underground coal mine. Low light …

Aiming at the issue that vehicle detection accuracy is easily influenced by abnormal weather
conditions such as rain, snow, and frog, et al. This paper studies the methods of expressway …

Vehicle detection in real-time scenarios is challenging because of the time constraints and
the presence of multiple types of vehicles with different speeds, shapes, structures, etc. This …

Today, the increase in the number of people, advances in industry and technology cause an
increase in the number of wastes generated with the acceleration of production. It is …

Traffic sign recognition technology is very important in intelligent transportation systems.
Aiming at the problem that the imbalance of existing traffic sign data sets affects the …