Results 241 to 250 of about 4,521,340 (293)

Ionic Liquid-Electrode Interface at Saturation: To Crowd, or Not to Crowd? [PDF]

J Phys Chem Lett
Nguyen BL, Roos Nerut E, Beditski A, Kongi N, Ivanistsev V, Voroshylova IV.   +5 more
europepmc   +1 more source

Quantum-inspired pedestrian mobility modeling: Applying probabilistic spatial simulation to urban walkability and thermal comfort in Sri Lanka. [PDF]

PLoS One
Deshan M, Jayasinghe A, Abenayake C.
europepmc   +1 more source

Towards real-world monitoring scenarios: An improved point prediction method for crowd counting based on contrastive learning. [PDF]

PLoS One
Cao R, Yu J, Liu Z, Liang Q.
europepmc   +1 more source

A lightweight convolutional neural network architecture for violence detection in video sequences. [PDF]

Sci Rep
Tyagi B, Jain R, Jain P, Priyadarsini RN, Sharma A.   +4 more
europepmc   +1 more source

Advanced COVID-19 detection using cough signals with space reconstruction and 3D deep convolutional neural networks. [PDF]

Sci Rep
Altae AA, Ehsani Rad A, Mohebbi K.
europepmc   +1 more source

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The Crowd is a Collaborative Network

Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, 2016
The main goal of this paper is to show that crowdworkers collaborate to fulfill technical and social needs left by the platform they work on. That is, crowdworkers are not the independent, autonomous workers they are often assumed to be, but instead work within a social network of other crowdworkers.
Mary L. Gray, Siddharth Suri, Syed Shoaib Ali, Deepti Kulkarni   +3 more
openaire   +1 more source

Adaptive weighted crowd receptive field network for crowd counting

Pattern Analysis and Applications, 2020
Crowd counting plays an important role in crowd analysis and monitoring. To this end, we propose a novel method called Adaptive Weighted Crowd Receptive Field Network (AWRFN) for crowd counting to estimate the number of people and the spatial distribution of input crowd images.
Sifan Peng, Luyang Wang, Baoqun Yin, Yun Li, Yinfeng Xia, Xiaoliang Hao   +5 more
openaire   +2 more sources

The Communication Network Within the Crowd

Proceedings of the 25th International Conference on World Wide Web, 2016
Since its inception, crowdsourcing has been considered a black-box approach to solicit labor from a crowd of workers. Furthermore, the "crowd" has been viewed as a group of independent workers dispersed all over the world. Recent studies based on in-person interviews have opened up the black box and shown that the crowd is not a collection of ...
Ming Yin 0001, Mary L. Gray, Siddharth Suri, Jennifer Wortman Vaughan   +3 more
openaire   +2 more sources

Social network of the competing crowd

2014 International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC2014), 2014
In this paper, we analyze the social network among competition participants at Kaggle.com. In particular, individuals, called members, are allowed to participate in various competition in teams. Each team may have one or more members. As a result, the relationship between teams and members may be represented as a bipartite graph.
Kai Lu, Wenjun Zhou 0001, Xuehua Wang
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Feature Reaggregation Network for Crowd Counting

2020 4th International Conference on Advances in Image Processing, 2020
In this paper, we propose a novel end-to-end network named Feature Reaggregation Network (FRNet) for crowd counting, which focuses on fusing the multi-scale features in the hierarchy for generating high-quality density maps. Two level and three level feature reaggregation modules are developed between the backbone network and the next feature ...
Xiaoliang Hao, Qianqian Yang, Yinfeng Xia, Baoqun Yin, Sifan Peng   +4 more
openaire   +1 more source