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- W2143755656 abstract "This work deals with multisensor data fusion to obtain landcover classification. The role of feature-level fusion using the Dempster-Shafer rule and that of data-level fusion in the MRF context is studied in this paper to obtain an optimally segmented image. Subsequently, segments are validated and classification accuracy for the test data is evaluated. Two examples of data fusion of optical images and a synthetic aperture radar image are presented, each set having been acquired on different dates. Classification accuracies of the technique proposed are compared with those of some recent techniques in literature for the same image data." @default.
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- W2143755656 date "2005-05-01" @default.
- W2143755656 modified "2023-10-18" @default.
- W2143755656 title "Landcover classification in MRF context using Dempster-Shafer fusion for multisensor imagery" @default.
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- W2143755656 doi "https://doi.org/10.1109/tip.2005.846032" @default.
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