Pedestrian detection remains a critical problem in various domains, such as computer
vision, surveillance, and autonomous driving. In particular, accurate and instant detection of …

The detection of pedestrians using infrared images is essential for security during automatic
driving and monitoring under low illumination or occlusion conditions. However, detecting …

Pedestrian detection is crucial for various applications, including intelligent transportation
and video surveillance systems. Although recent research has advanced pedestrian …

An anchor-free infrared pedestrian detection algorithm is proposed to address the problems
of multiscale, partial occlusion and environmental interference in infrared images, which …

Vehicle classification is a challenging task in the area of image processing. It involves the
classification of various vehicles based on their color, model, and make. A distinctive variety …

Personnel detection in a coal mine is of great significance for monitoring the safety and real-
time positioning of underground personnel. However, the uneven illumination, large dust …

Traffic signs and road objects detection is a significant issue for driver safety. It has become
popular with the development of autonomous vehicles and driver-assistant systems. This …

Nowadays, the reliability of data analysis and decision-making based on deep learning (DL)
remains a primary concern in promoting DL technology for industrial non-destructive testing …

Nowadays, Deep Neural Networks are very popular for solving computer vision problems.
The motivation of this study is to explore the different deep learning-based architectures …

The definition of pedestrian behavior when crossing the street and facing potential collision
situations is crucial for the design of new Autonomous Emergency Braking systems (AEB) in …