Low Complexity Recruitment for Collaborative Mobile Crowdsourcing Using
Graph Neural Networks

Low Complexity Recruitment for Collaborative Mobile Crowdsourcing Using Graph Neural Networks

IEEE Internet of Things Journal (IEEE IoT Journal), 2021

1 June 2021

ArXiv (abs)PDF HTML

Papers citing "Low Complexity Recruitment for Collaborative Mobile Crowdsourcing Using Graph Neural Networks"

4 / 4 papers shown

Title
Resource Allocation in Hybrid Radio-Optical IoT Networks using GNN with Multi-task Learning Aymen Hamrouni S. Pollin Hazem Sallouha 44 0 0 29 Oct 2025
A Semi-supervised Sensing Rate Learning based CMAB Scheme to Combat COVID-19 by Trustful Data Collection in the CrowdComputer Communications (Comput. Commun.), 2023 Jianheng Tang Kejia Fan Wenxuan Xie Luomin Zeng Feijiang Han Guosheng Huang Tian Wang Anfeng Liu Shaobo Zhang 94 6 0 17 Jan 2023
A Hybrid Artificial Neural Network for Task Offloading in Mobile Edge ComputingMidwest Symposium on Circuits and Systems (MWSCAS), 2022 Raby Hamadi Abdullah Khanfor Hakim Ghazzai Y. Massoud 135 4 0 06 Jun 2022
Service Discovery in Social Internet of Things using Graph Neural NetworksMidwest Symposium on Circuits and Systems (MWSCAS), 2022 Aymen Hamrouni Hakim Ghazzai Y. Massoud 194 12 0 25 May 2022