Results 241 to 250 of about 318,999 (276)

Routing few robots in a crowded network

Journal of Computer and System Sciences
In Graph Coordinated Motion Planning, we are given a graph G some of whose vertices are occupied by robots, and we are asked to route k marked robots to their destinations while avoiding collisions and without exceeding a given budget 𝓁 on the number of robot moves.
Deligkas, Argyrios, Eiben, Eduard, Ganian, Robert, Kanj, Iyad, Leko, Dominik, Ramanujan, M. S.   +5 more
openaire   +2 more sources

Dense Crowd Counting with Capsule Networks

2020 International Conference on Systems, Signals and Image Processing (IWSSIP), 2020
In this paper, we proposed and evaluated the adoption of a capsule network-based (CapsNet-based) model rather than the convolutional neural network-based (CNN-based) models which are predominant in crowd counting tasks. The aim is to join the task of generating a high-quality density map from a single image along with producing a more precise estimate ...
Victor Hugo Roldão Reis, Silvio Jamil Ferzoli Guimarães, Zenilton Kleber Gonçalves do Patrocínio Jr.   +2 more
openaire   +1 more source

Relational Attention Network for Crowd Counting

2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019
Crowd counting is receiving rapidly growing research interests due to its potential application value in numerous real-world scenarios. However, due to various challenges such as occlusion, insufficient resolution and dynamic backgrounds, crowd counting remains an unsolved problem in computer vision.
Anran Zhang, Jiayi Shen, Zehao Xiao, Fan Zhu 0001, Xiantong Zhen, Xianbin Cao 0001, Ling Shao 0001   +6 more
openaire   +1 more source

A scale adaptive network for crowd counting

Neurocomputing, 2019
Abstract Scale variations occur frequently and present a great challenge for crowd counting in practical applications. In this paper, we propose a scale adaptive network to address the scale variation problem for crowd counting. We design a scale expansion unit which uses normal and dilated convolution to expand the receptive field size range of its ...
Youmei Zhang, Chunluan Zhou, Faliang Chang, Alex C. Kot   +3 more
openaire   +1 more source

Small Cells Placement for Crowd Networks

2018 IEEE International Conference on Communications (ICC), 2018
The deployment of small cells is one of the technical solutions to meet the challenge of data traffic rise. It reduces the cost of radio access networks. The efficiency of this solution depends on the success of cell planning to mitigate the interference. This work aims to optimize the incremental cell planning scheme that considers a preliminary macro-
Dhifallah, Khaoula, Gourhant, Yvon, Senouci, Sidi-Mohammed, Morand, Lionel   +3 more
openaire   +2 more sources

Aggregating information from the crowd and the network

Proceedings of the 22nd International Conference on World Wide Web, 2013
In social systems, information often exists in a dispersed manner, as individual opinions, local insights and preferences. In order to make a global decision however, we need to be able to aggregate such local pieces of information into a global description of the system.
openaire   +1 more source

Scale Pyramid Network for Crowd Counting

2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 2019
Crowd counting is a concerned yet challenging task in computer vision. The difficulty is particularly pronounced by scale variations in crowd images. Most state-of-art approaches tackle the multi-scale problem by adopting multi-column CNN architectures where different columns are designed with different filter sizes to adapt to variable pedestrian ...
Xinya Chen, Yanrui Bin, Nong Sang, Changxin Gao   +3 more
openaire   +1 more source

Dynamic Camera Network Reconfiguration for Crowd Surveillance

Proceedings of the 12th International Conference on Distributed Smart Cameras, 2018
Crowd surveillance will play a fundamental role in the coming generation of video surveillance systems, in particular for improving public safety and security. However, traditional camera networks are mostly not able to closely survey the entire monitoring area due to limitations in coverage, resolution and analytics performance. A smart camera network,
Bisagno, Niccoló, Conci, Nicola, Rinner, Bernhard   +2 more
openaire   +2 more sources

Jointly attention network for crowd counting

Neurocomputing, 2022
Yuqiang He, Yinfeng Xia, Yizhen Wang, Baoqun Yin   +3 more
openaire   +1 more source

A survey of crowd counting and density estimation based on convolutional neural network

Neurocomputing, 2022
Zheng Zhang, Guangming Lu, Yu-Dong Zhang
exaly