reference-cover

Earlier we have written about assessing classification accuracy. The post dealt with creating confusion matrix. But the topic is not resolved with that as it has some more interesting points. While assessing the accuracy of automated classification results one has to answer these two questions: which assessment method should be selected? where and how to […]

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confusion-matrix

Applying any classification algorithm to interpret a remotely sensed image we are always interested in the result accuracy. The simplest way to assess it is the visual evaluation. Comparing the image with the results of its interpretation, we can see errors and roughly estimate their size. But if we need a reliable accuracy assessment, we […]

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