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Maximizing Data Credibility Under Budget Constraint for Participatory Sensing., , , , , и . HPCC/CSS/ICESS, стр. 134-139. IEEE, (2015)Ensuring High-Quality Data Collection for Mobile Crowd Sensing., , , , и . WCNC, стр. 1-6. IEEE, (2017)Participant Selection for Federated Learning With Heterogeneous Data in Intelligent Transport System., , , , и . IEEE Trans. Intell. Transp. Syst., 24 (1): 1106-1115 (января 2023)Energy-Efficient Distributed Mobile Crowd Sensing: A Deep Learning Approach., , и . IEEE J. Sel. Areas Commun., 37 (6): 1262-1276 (2019)Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation., , , , и . CoRR, (2023)EdgeVisionBench: A Benchmark of Evolving Input Domains for Vision Applications at Edge., , , , и . ICDE, стр. 3643-3646. IEEE, (2023)On the Difficulty of Unpaired Infrared-to-Visible Video Translation: Fine-Grained Content-Rich Patches Transfer., , , , и . CVPR, стр. 1631-1640. IEEE, (2023)Route Capacity Estimation Based Admission Control and QoS Routing for Mesh Networks., , и . GLOBECOM, стр. 1-6. IEEE, (2009)Crowdsourcing energy-efficient participants to ensure quality-of-information., , , , and . PIMRC, page 1606-1610. IEEE, (2015)Adaptive working schedule for duty-cycle opportunistic mobile networks., , , and . ICC, page 1565-1569. IEEE, (2013)