Deep learning approach for radar-based people counting
JH Choi, JE Kim, KT Kim - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
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 …
DL-based algorithms have outperformed handcrafted feature (HF)-based ones in various …
Accurate people counting based on radar: Deep learning approach
JH Choi, JE Kim, NH Jeong, KT Kim… - 2020 IEEE Radar …, 2020 - ieeexplore.ieee.org
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 …
learning (DL) approach. The DL algorithm is a great tool that enables the automatic …
Radar-based people counting under heterogeneous clutter environments
JH Choi, JE Kim, KT Kim - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Radar-based people counting (RPC) systems, which perceive their surroundings through
wireless reflections from radar, can provide crowd information free from privacy invasion and …
wireless reflections from radar, can provide crowd information free from privacy invasion and …
Multi-modal cross learning for improved people counting using short-range FMCW radar
Radar systems enable remote-less sensing of multiple persons in its field of view. In this
paper, we propose a novel people counting system using 60-GHz frequency modulated …
paper, we propose a novel people counting system using 60-GHz frequency modulated …
Person head detection based deep model for people counting in sports videos
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 …
surveillance. People counting in these venues faces many key challenges, such as severe …
Towards more effective prm-based crowd counting via a multi-resolution fusion and attention network
The paper focuses on improving the recent plug-and-play patch rescaling module (PRM)
based approaches for crowd counting. In order to make full use of the PRM potential and …
based approaches for crowd counting. In order to make full use of the PRM potential and …
Counting people inside a region-of-interest in CCTV footage with deep learning
B Pardamean, F Abid, TW Cenggoro… - PeerJ Computer …, 2022 - peerj.com
In recent years, the performance of people-counting models has been dramatically
increased that they can be implemented in practical cases. However, the current models can …
increased that they can be implemented in practical cases. However, the current models can …
Cross-level parallel network for crowd counting
Automated people counting in crowd scenes is challenging due to large variations in scale,
density, and background clutter. To tackle them, we propose a novel cross-level parallel …
density, and background clutter. To tackle them, we propose a novel cross-level parallel …
Robust people counting using sparse representation and random projection
Estimating the number of people present in an image has many practical applications
including visual surveillance and public resource management. Recently, regression-based …
including visual surveillance and public resource management. Recently, regression-based …
Dense people counting using IR-UWB radar with a hybrid feature extraction method
X Yang, W Yin, L Li, L Zhang - IEEE Geoscience and Remote …, 2018 - ieeexplore.ieee.org
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 …
ultrawideband radar has been extensively adopted to count people because it provides a …