To alleviate the spread of the epidemic, most public places have begun to limit the number
of trips. Therefore, this article proposes a pedestrian counting scheme based on YOLOv5 …

In order to realize real-time and accurate population statistics of pedestrians in video, a
counting method based on deep learning is proposed. Firstly, the anchor boxes of the …

To solve the problem of low counting efficiency of people flow supervision in scenic spots
and cities, an improved YOLOv5s detection method combined with DeepSORT target …

Crowd monitoring has been gaining attention among researchers for a wide range of
applications. Such applications may include abnormal behavior detection for security …

Researchers are becoming more interested in crowd surveillance because of its several
potential applications. These applications may include detecting unusual activity for security …

With the great success of deep learning in the field of machine vision, crowd density
statistics based on machine vision have become more and more important in today's world …

The bus passenger data are very important for urban bus dispatching management. When
passengers get on or off the bus, they often hide from each other. It is a great challenge for …

Accurate pedestrian counting algorithm is critical to eliminate insecurity in the congested
public scenes. However, counting pedestrians in crowded scenes often suffer from severe …

In the last decade, the application of pedestrian detection in computer vision has gradually
increased, such as social distance detection in the epidemic era. In this paper, we improve …

Pedestrian detection is an important branch of object detection due to its various
applications. It plays a vital role in many fields such as intelligent surveillance systems. The …