Recent progress in deep learning has led to accurate and efficient generic object detection
networks. Training of highly reliable models depends on large datasets with highly textured …

To solve object detection issues in infrared images, such as a low recognition rate and a
high false alarm rate caused by long distances, weak energy, and low resolution, we …

Global terrorist threats and illegal migration have intensified concerns for the security of
citizens, and every effort is made to exploit all available technological advances to prevent …

Pedestrian detection is an important but challenging problem in computer vision, especially
in human-centric tasks. Over the past decade, significant improvement has been witnessed …

Gestures have been used for nonverbal communication for a long time, but human–
computer interaction (HCI) via gestures is becoming more common in the modern era. To …

Visible–infrared object detection aims to improve the detector performance by fusing the
complementarity of visible and infrared images. However, most existing methods only use …

Pedestrian Detection is the most critical module of an Autonomous Driving system. Although
a camera is commonly used for this purpose, its quality degrades severely in low-light night …

Although the visual appearances of small-scale objects are not well observed, humans can
recognize them by associating the visual cues of small objects from their memorized …

Pedestrian detection is a core problem in computer vision that sees broad application in
video surveillance and, more recently, in advanced driving assistance systems. Despite its …

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