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The spatial combination (overlays) for the classifications results in seed zones combining attributes represented by the three canonical variates.
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The classification results are presented in the conclusion part.
The classification results obtained show an overall accuracy of 90.2%.
The classification results associated with these handcrafted features is lower compared to the ConvNet classifier and also results in more variability.
To reduce the bias in the classification results we equalized the number of units for each classifier to be the same.
First, we pooled the three pattern strengths defined above and found that the classification results remain good (accuracy 79%; Supplement Note 4).
Lower concordance of the classification results (by STORK) for the Universidad de Valencia dataset could be related to different grading systems used by that clinic.
Table 2 summarizes the classification results.
The classification results presented in Section 5.1.
Figure 2 shows the classification results of the Lena image.
The localization result is obtained according to the classification results.
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