Table 5. Experimental results for multi-class classification(NC, vmiD, miD, mD).
Methods | Performance metrics | ||
---|---|---|---|
Accu | Sens | Spec | |
Deep-Ensemble (Loddo, Buttau & Di Ruberto,2022) | 0.971 | 0.967 | 0.982 |
Neural Nets with VGG16 (Sharma et al., 2022) | 0.904 | 0.905 | 0.904 |
AlexNet (Loddo, Buttau & Di Ruberto,2022) | 0.893 | 0.906 | 0.817 |
ResNet-101 (Loddo, Buttau & Di Ruberto,2022) | 0.965 | 0.978 | 0.961 |
Inception-ResNet-v2 (Loddo, Buttau & Di Ruberto,2022) | 0.897 | 0.901 | 0.856 |
(Our Methodology) | 0.982 | 0.982 | 0.989 |