With the progress of scientific-technology, automatic equipment has become a prevailing
trend in our society. Especially in transportation, unmanned vehicle system is a significant …

Computer vision technology for detecting objects in a complex environment often includes
other key technologies, including pattern recognition, artificial intelligence, and digital image …

Object detection is one of the most challenging problems in the field of computer vision, the
practicality of object detection requires accuracy and real-time. YOLOv3 is a good real-time …

With the development of deep learning, object detection has made substantial progress.
However, when the object to be detected in the image is small or partially occluded, the …

Object detection is a crucial aspect of computer vision, and deep learning has led to
significant advancements in this area. Object categorization, segmentation, and localization …

YOLOv3 is a deep learning-based real-time object detector and is mainly used in
applications such as video surveillance and autonomous vehicles. In this paper, we …

This paper explicates the systematic advancements that were observed from the inception of
the YOLO (You Only Look Once) object detector to the most recent version 4. Since its …

Object detection with high accuracy and fast inference speed based on camera sensors is
important for autonomous driving. This paper develops a lightweight object detection …

To solve real-life problems for different smart city applications, using deep Neural Network,
such as parking occupancy detection, requires fine-tuning of these networks. For large …

The YOLOv4 approach has gained significant popularity in industrial object detection due to
its impressive real-time processing speed and relatively favorable accuracy. However, it has …