HAGN: Hierarchical Attention Guided Network for Crowd Counting
IEEE Access, 2020 In recent years, deep learning based crowd counting networks have achieved significant progress. However, most of them generate rough crowd density maps due to low-resolution features used for estimating crowd distribution, which affects the performance ...
Zuodong Duan, Yujun Xie, Jiahao Deng
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Detection of High-Density Crowds in Aerial Images Using Texture Classification
Remote Sensing, 2016 Automatic crowd detection in aerial images is certainly a useful source of information to prevent crowd disasters in large complex scenarios of mass events.
Oliver Meynberg +2 more
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Short-time existence of solutions for mean-field games with congestion [PDF]
, 2015 We consider time-dependent mean-field games with congestion that are given by a system of a Hamilton-Jacobi equation coupled with a Fokker-Planck equation. The congestion effects make the Hamilton-Jacobi equation singular.
Gomes, Diogo, Voskanyan, Vardan
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A Statistical Approach in Designing an RF-Based Human Crowd Density Estimation System
International Journal of Distributed Sensor Networks, 2016 The study of human crowd density estimation (H-CDE) using radio frequency is limited due to the nature of wireless medium and the advancement of visual-based systems.
S. Y. Fadhlullah, Widad Ismail
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A system for efficient egress scheduling during mass events and small-scale experimental demonstration [PDF]
Royal Society Open Science, 2020 Improvements in the design of pedestrian facilities have reduced the frequency of crowd accidents, and safety is now generally ensured in well-planned crowd events. However, congestion and inefficient use of infrastructures still remain an issue.
Hisashi Murakami +3 more
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ResnetCrowd: a residual deep learning architecture for crowd counting, violent behaviour detection and crowd density level classification [PDF]
, 2017 In this paper we propose ResnetCrowd, a deep residual architecture for simultaneous crowd counting, violent behaviour detection and crowd density level classification.
Little, Suzanne +3 more
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DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density Estimation
, 2018 In real-world crowd counting applications, the crowd densities vary greatly in spatial and temporal domains. A detection based counting method will estimate crowds accurately in low density scenes, while its reliability in congested areas is downgraded ...
Gao, Chenqiang +3 more
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Holistic features for real-time crowd behaviour anomaly detection [PDF]
, 2016 This paper presents a new approach to crowd behaviour anomaly detection that uses a set of efficiently computed, easily interpretable, scene-level holistic features.
Little, Suzanne +3 more
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InformationAutomated crowd counting is a crucial aspect of surveillance, especially in the context of mass events attended by large populations. Traditional methods of manually counting the people attending an event are error-prone, necessitating the development of
Abdullah N Alhawsawi +2 more
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Evolution models for mass transportation problems [PDF]
, 2012 We present a survey on several mass transportation problems, in which a given mass dynamically moves from an initial configuration to a final one.
A. Brancolini +21 more
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