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• W2894591907 startingPage "3286" @default.
• W2894591907 abstract "Foggy days pose many difficulties for outdoor camera surveillance systems. On foggy days, the optical attenuation and scattering effects of the medium significantly distort and degenerate the scene radiation, making it noisy and indistinguishable. Aiming to solve this problem, in this paper we propose a novel object detection method that has the ability to exploit the information in the color and depth domains. To prevent the error propagation problem, we clean the depth information before the training process and remove false samples from the database. A domain adaptation strategy is employed to adaptively fuse the decisions obtained in the color and depth domains. In the experiments, we evaluate the contribution of the depth information for object detection on foggy days. Moreover, the advantages of the multiple-domain adaptation strategy are experimentally demonstrated via comparison with other methods." @default.
• W2894591907 created "2018-10-12" @default.
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• W2894591907 date "2018-09-30" @default.
• W2894591907 modified "2023-10-14" @default.
• W2894591907 title "Domain Adaptation and Adaptive Information Fusion for Object Detection on Foggy Days" @default.
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• W2894591907 doi "https://doi.org/10.3390/s18103286" @default.
• W2894591907 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6210270" @default.
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• W2894591907 hasPublicationYear "2018" @default.
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