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• W3005196854 abstract "Cloud detection is a complicated problem and attracts more and more attentions. To accomplish the task, a novel automatic supervised approach based on the scheme is recently proposed. It adopts traditional training and testing scheme, but regards each pixel of scenes in training image as a sample. It contains two main modules: feature data simulating, cloud detector learning and applying. The method achieves better results than other existing methods, however, since it adopts a linear classifier, the detection results may be influenced by the field points, which will limit its wider applications. To avoid the problem, a normalized-linear cloud detector is designed to improve the scene learning scheme. The new detector is designed based on logistic regression, and it could effectively suppress the influence caused by the field data. Comparisons of qualitative and quantitative analyses of the experimental results are implemented. Results indicate the efficacy of the proposed method." @default.
• W3005196854 created "2020-02-14" @default.
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• W3005196854 date "2019-07-01" @default.
• W3005196854 modified "2023-10-05" @default.
• W3005196854 title "An Improved Scene Learning Method for Cloud Detection Based on NormalizedLinear Detector" @default.
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• W3005196854 doi "https://doi.org/10.1109/icivc47709.2019.8981064" @default.
• W3005196854 hasPublicationYear "2019" @default.
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