Figure A8.

Illustrates a comparison of confusion matrices obtained through cascade generalization, utilizing the probability outputs of the ResNet50 model. (a) Confusion matrix for classification using only the ResNet50 model (DL-only, level-0); (b) Confusion matrix for classification utilizing the ResNet50 probability outputs and hand-crafted features, obtained through an ensemble of conventional classifiers (averaging); (c) Confusion matrix for classification using the ResNet50 (level-0) probability outputs and hand-crafted features for the best conventional classifier, random forest. All confusion matrices are generated after applying a threshold of 0.5 to the model’s probability outputs to obtain the final predictions.