Table 9 Exp1—classification of combined features using Histogram + PCA representation
From: Machine learning techniques for diabetic macular edema (DME) classification on SD-OCT images
Metric of combined features | ||||
|---|---|---|---|---|
HoG\(^{~PCA}\) + | ||||
Classifier | Metric | LBP\(_{8{\text{-}}\mathrm{ri}}^{\mathrm{PCA}}\) | HoG\(_{16{\text{-}}\mathrm{ri}}^{\mathrm{PCA}}\) | HoG\(_{24{\text{-}}\mathrm{ri}}^{\mathrm{PCA}}\) |
Linear-SVM | SE | 68.7 | 75.0 | 68.7 |
SP | 81.2 | 87.5 | 87.5 | |
RBF-SVM | SE | 68.7 | 18.7 | 0 |
SP | 81.2 | 93.7 | 100.0 | |
RF | SE | 62.5 | 75.0 | 62.5 |
SP | 81.2 | 87.5 | 87.5 | |