Object detection using deep learning, one of the most challenging problems in computer vision, seeks to locate instances of objects from a large number of predefined categories in natural images.

Salient object detection in optical remote sensing images (RSI-SOD) has recently become a key area of research, driven by the unique challenges posed by specific imaging conditions. Traditional ...

The study of computer systems and software that can recognize and understand scenes and images is known as computer vision. Image recognition, object detection, image synthesis, image super resolution ...

It is important to build robust object detector (ROD) in real-world applications because snow, rain, fog, motion blur, and various kinds of corruption can occur in autonomous-driving environments.

Object detection has shown noticeably rapid improvement, despite most existing methods still scrabbling in occluded object detection. In response to this problem, this paper proposes a method for ...

Object recognition along with classification are necessary for many applications, such as surveillance systems, car plate recognition, traffic monitoring, and face detection. Unlike existing ...

With the rise of autonomous driving, LiDAR-based object detection using deep neural networks (DNNs) has shown exceptional performance. However, DNNs are vulnerable to adversarial attacks, especially ...

Outlier traffic flow detection under unplanned disruptions is vital for operational safety and management. Though numerous models have been proposed to effectively detect outlier traffic flow in ...