In this study, a novel radar-based people counting (PC) method is presented using the deep
learning (DL) approach. The DL algorithm is a great tool that enables the automatic …

With the development of deep learning (DL) frameworks in the field of pattern recognition,
DL-based algorithms have outperformed handcrafted feature (HF)-based ones in various …

Counting the number of people is a common and basic computing operation in many
applications. Most of the people counting techniques need a sensing device like camera …

Radar-based people counting (RPC) systems, which perceive their surroundings through
wireless reflections from radar, can provide crowd information free from privacy invasion and …

The number of people in a crowd is crucial information in public safety, intelligent
monitoring, traffic management, architectural design, and other fields. At present, the …

Due to its portability and maneuverability, Unmanned Aerial Vehicles (UAVs) are
increasingly used in industrial fields. Our work aims to develop a framework of person …

In the field of crowd counting, the current mainstream CNNbased regression methods simply
extract the density information of pedestrians without finding the position of each person …

People counting in sports venues is emerging as a new domain in the field of video
surveillance. People counting in these venues faces many key challenges, such as severe …

Radar systems enable remote sensing of multiple persons within their field of view. In this
paper, we propose a novel architecture to perform people counting using a 60 GHz …

Owing to the increased use of urban rail transit, the flow of passengers on metro platforms
tends to increase sharply during peak periods. Monitoring passenger flow in such areas is …