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Accuracy of Classified Imagery without using Reference Data Set

机译:不使用参考数据集的分类图像的准确性

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for the validation aspect the estimation of accuracy of classifiers is significant factor of analyzing the result of classifiers. If the pixel found in single class. So we prefer the hard classification. But satellite data does not find in single class. The pixel of satellite data belongs more than one class. So in that case we prefer the soft classification. The classification is only one parameter and other parameter is assessment of accuracy and we know without assessment of accuracy classification of classifiers is incomplete. There are several method to find out the the accuracy of classifiers like MLC, FERM, RMSE, and Entropy. Accuracy results are generated for soft classified data set from AWiFS, LISS-III and LISS-IV sensor. The output results from tool used to investigation effect of sampling on assessed accuracy
机译:对于验证方面,分类器准确性的估计是分析分类器结果的重要因素。如果在单类中找到的像素。所以我们更喜欢坚硬的分类。但卫星数据在单级中找不到。卫星数据的像素属于多个类。所以在这种情况下,我们更喜欢软分类。分类只是一个参数,其他参数是对准确性的评估,我们知道没有评估分类器的准确性分类是不完整的。有几种方法可以了解MLC,FERM,RMSE和熵等分类器的准确性。为来自AWIFS,Liss-III和Liss-IV传感器的软分类数据集生成精度结果。用于调查采样对评估准确性的效果的工具的输出结果

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