2022
DOI: 10.1109/ojvt.2022.3205422
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Hybrid Data Selection With Context and Content Features for Visual Crowdsensing

Abstract: Visual crowdsensing (VCS) is becoming predominant in mobile crowdsensing, but there still exist various unique challenges, including large sizes of visual data, multidimensional requirements, and intensive processing demands. As a key research problem in VCS, data selection filters out redundant data and only retains most representative samples, which can effectively reduce the complexity and cost for VCS. In this paper, we study a phase-by-phase data selection approach, in which metadata are first used to pre… Show more

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