Results 31 to 40 of about 318,999 (276)
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank [PDF]
, 2019 For many applications the collection of labeled data is expensive laborious. Exploitation of unlabeled data during training is thus a long pursued objective of machine learning.
Bagdanov, Andrew D. +2 more
core +2 more sources
A Deep-Fusion Network for Crowd Counting in High-Density Crowded Scenes [PDF]
International Journal of Computational Intelligence Systems, 2021 AbstractPeople counting has been investigated extensively as a tool to increase the individual’s safety and to avoid crowd hazards at public places. It is a challenging task especially in high-density environment such as Hajj and Umrah, where millions of people gathered in a constrained environment to perform rituals. This is due to large variations of
Sultan Daud Khan +3 more
openaire +1 more source
A Data-Driven Urban Metro Management Approach for Crowd Density Control
Journal of Advanced Transportation, 2021 Large crowding events in big cities pose great challenges to local governments since crowd disasters may occur when crowd density exceeds the safety threshold.
Hui Zhou +4 more
doaj +1 more source
Crowd counting using a self‐attention multi‐scale cascaded network
IET Computer Vision, 2019 Recent developments of crowd analysis and behaviour prediction have attracted much attention. Crowd counting, as the essential and challenging task in crowd analysis, is riddled with many issues, such as large scale variations, serious occlusion, and so ...
He Li, Shihui Zhang, Weihang Kong
doaj +1 more source
Detection of Salient Crowd Motion Based on Repulsive Force Network and Direction Entropy
Entropy, 2019 This paper proposes a method for salient crowd motion detection based on direction entropy and a repulsive force network. This work focuses on how to effectively detect salient regions in crowd movement through calculating the crowd vector field and ...
Xuguang Zhang +5 more
doaj +1 more source
Redesigned Skip-Network for Crowd Counting with Dilated Convolution and Backward Connection
Journal of Imaging, 2020 Crowd counting is a challenging task dealing with the variation of an object scale and a crowd density. Existing works have emphasized on skip connections by integrating shallower layers with deeper layers, where each layer extracts features in a ...
Sorn Sooksatra +3 more
doaj +1 more source
An urban crowd flow model integrating geographic characteristics
Scientific Reports, 2023 Predicting urban crowd flow spatial distributions plays a critical role in optimizing urban public safety and traffic congestion management. The spatial dependency between regions and the temporal dynamics of the local crowd flow are two important ...
Yu Zhang +4 more
doaj +1 more source
Crowd Behavior Recognition Using Hybrid Tracking Model and Genetic algorithm Enabled Neural Network
International Journal of Computational Intelligence Systems, 2017 In the current era, crowd behavior analysis is important topic due to the significance of video surveillance in the public area. Literature presents a handful of works for crowd behavior detection and analysis.
Manoj Kumar, Charul Bhatnagar
doaj +1 more source
IET Image Processing, 2021 Since the era of we‐media, live video industry has shown an explosive growth trend. For large‐scale live video streaming, especially those containing crowd events that may cause great social impact, how to identify and supervise the crowd activity in ...
Junpeng Kang +3 more
doaj +1 more source
COVID-19 Spread Simulation in a Crowd Intelligence Network
International Journal of Crowd Science, 2022 In this paper, the Crowd Intelligence Network Model is applied to the simulation of epidemic spread. This model combines the multi-layer coupling network model and the two-stage feedback member model to study the epidemic spread mechanisms under multiple-
Linzhi Shan, Hongbo Sun
doaj +1 more source