An implementation architecture for crowd network simulations
International Journal of Crowd Science, 2020 PurposeCrowd network systems have been deemed as a promising mode of modern service industry and future economic society, and taking crowd network as the research object and exploring its operation mechanism and laws is of great significance for ...
Jialin Zou, Kun Wang, Hongbo Sun
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Improved Crowd Counting Method Based on Scale-Adaptive Convolutional Neural Network
IEEE Access, 2019 Crowd counting is a challenging task due to the influence of various factors, such as scene transformation, complex crowd distribution, uneven illumination, and occlusion.
Jun Sang +6 more
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Scene Adaptive Segmentation for Crowd Counting in Population Heterogeneous Distribution
Applied Sciences, 2022 Crowd counting is an important part of crowd analysis and has been widely applied in the field of public safety and commercial management. Although researchers have proposed many crowd counting methods, there is little research on non-uniform population ...
Hui Gao +3 more
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A Multi-scale Crowd Counting Algorithm with Removing Background Interference [PDF]
Jisuanji gongcheng, 2022 Crowd counting technology is aimed at estimating the number of people in crowd pictures or videos.The technology can effectively be applied to prevent stampede accidents and is widely used in security and early warning, urban planning, and management of ...
GUO Aixin, XIA Yinfeng, WANG Dawei, LU Bin
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Intelligence level analysis for crowd networks based on business entropy [PDF]
International Journal of Crowd Science, 2019 Purpose – Intelligence level of a crowd network is defined as the expected reward of the network when completing the latest tasks (e.g. last N tasks).
Zhouxia Li +4 more
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Crowd Counting Algorithm Based on Feature Pyramid Network [PDF]
Jisuanji gongcheng, 2019 The single-picture crowd count has a sharp decline in performance due to severe population occlusion and scale changes.Therefore,this paper proposes an algorithm for crowd counting pictures,and gives a Full Convolution Network(FCN) capable of processing ...
MA Hao, YIN Baoqun, PENG Sifan
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Crowd Density Detection Technology Based on Deep Semantic Segmentation
Jisuanji kexue yu tansuo, 2021 With the development of society, people are going out more and more, which leads to more and more crowded scenes. The detection of crowd density is particularly important.
MA Yu, DU Huimin, MAO Zhili, ZHANG Xia
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Robot-Assisted Crowd Evacuation Algorithm Based on Deep Spatio-Temporal Q-network [PDF]
Jisuanji gongcheng, 2021 The application of robots to crowd evacuation is limited by the low flexibility, low scenario adaptability, and low evacuation efficiency of robots.To address the problem, this paper proposes an algorithm for robot-assisted crowd evacuation based on deep
TAN Mei, LIU Shihao, ZHOU Wan, CHEN Guowen, HU Xuemin
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Adaptive information sharing approach for crowd networks based on two stage optimization [PDF]
International Journal of Crowd Science, 2019 Purpose – This paper aims to optimize and evaluating the performance of the crowd networks through analyzing their information sharing patterns. That is, in a crowd network, the qualities of accomplishing tasks are highly dependent on the effective ...
Xiaoni Wang +4 more
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A Crowd Equivalence-Based Massive Member Model Generation Method for Crowd Science Simulations
International Journal of Crowd Science, 2022 Crowd phenomena are widespread in human society, but they cannot be observed easily in the real world, and research on them cannot follow traditional ways. Simulation is one of the most effective means to support studies about crowd phenomena.
Aoqiang Xing, Hongbo Sun
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