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Functional Dissipation Classification of Retinal Images

机译:视网膜图像的功能耗散分类

摘要

Retinal images can be classified by selecting a classifier and a figure of merit for quantifying classification quality; selecting a transform to generate features from input data; using a recursive process of functional dissipation to generate dissipative features from the features generated according to the transform; computing the figure of merit for all of the dissipative features generated; searching for at least one of the dissipative features that maximize the figure of merit on a training set; and classifying a test set with the classifier by using the “at least one of the dissipative features.”
机译:可以通过选择分类器和品质因数来对视网膜图像进行分类以量化分类质量;选择转换以从输入数据生成特征;使用功能耗散的递归过程从根据变换生成的特征中生成耗散特征;计算所产生的所有耗散特征的品质因数;搜索至少一个使训练集的品质因数最大化的耗散特征;并使用“至少一种耗散特征”使用分类器对测试集进行分类。

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