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- W2058252362 abstract "Abstract This study focuses on conflation procedures to enhance classification accuracy for remote sensing imagery. In this context, conflation refers to the merging of the most accurate portions of a set of classified images to yield a result that is more accurate than any individual image. Two main types of conflation procedures are discussed. The first is a heuristic approach based on if‐then rules and the second is based on statistical manipulation of misclassification probabilities. The conflation procedures are tested on three classified images derived from a high‐resolution multispectral video mosaic using non‐traditional classification methods. For these test data, conflation yields improvements in classification accuracy of up to 15 percent." @default.
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- W2058252362 date "2000-03-01" @default.
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- W2058252362 title "Enhancement of Classification Accuracy Using Conflation Procedures" @default.
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- W2058252362 doi "https://doi.org/10.1080/10106040008542135" @default.
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