Table 6 Performance of ensemble combinations using googlenet, DenseNet-121, VGG16, and ResNet-34.
From: Deep learning-based automatic diagnosis of rice leaf diseases using ensemble CNN models
Model Combination | Accuracy (%) | F1-Score | MCC |
|---|---|---|---|
GoogLeNet + DenseNet-121 | 95.70 | 0.954 | 0.936 |
VGG16 + ResNet-34 | 95.35 | 0.951 | 0.932 |
GoogLeNet + VGG16 + DenseNet-121 | 96.32 | 0.961 | 0.944 |
GoogLeNet + VGG16 + DenseNet-121 + ResNet-34 | 96.81 | 0.967 | 0.952 |
