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 …

In this paper, we propose system based on impulse radio ultra-wideband (IR-UWB) radar
sensors for counting multiple people passing through a passage or a wide door. The …

In recent years, various researches have been conducted in order to find ways to cover a
target or groups of targets with priority-based target coverage and sensor deployment …

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 …

Sensor networks have been used in many surveillance systems, providing statistical
information about monitored areas. Accurate counting information (eg, the distribution of the …

Reliable people counting is crucial to many urban applications. However, most existing
people counting systems are sensor-based and can only work in some fixed gateways or …

People counting serves a vital role in sensing applications. Impulse radio ultra-wideband (IR-
UWB) radar, which has strong penetration and high-range resolution, has been extensively …

Crowd counting, which count or accurately estimate the number of human beings within a
region, is critical in many applications, such as guided tour, crowd control and marketing …

People counting is one of the hottest issues in sensing applications. Impulse radio
ultrawideband radar has been extensively adopted to count people because it provides a …

This paper focuses on the problem of providing a rough count of the number of people in a
room using passive WiFi Channel State Information (CSI) measurements taken by a single …