Table 4 Overall performances (%) of the proposed PND-Net built upon different standard base CNNs.
From: PND-Net: plant nutrition deficiency and disease classification using graph convolutional network
Dataset | Base CNN + GCN | Top-1 accuracy | Top-3 accuracy | Precision | Recall | F1-score |
|---|---|---|---|---|---|---|
Banana | ResNet-50 | 90.00 | 98.34 | 90.00 | 90.00 | 90.00 |
Xception | 89.25 | 98.27 | 90.00 | 89.00 | 89.00 | |
Inception-V3 | 83.77 | 98.13 | 84.00 | 84.00 | 84.00 | |
MobileNet-V2 | 83.99 | 97.80 | 84.00 | 84.00 | 83.00 | |
Coffee | ResNet-50 | 89.52 | 97.00 | 89.00 | 89.00 | 89.00 |
Xception | 90.54 | 98.67 | 90.00 | 90.00 | 90.00 | |
Inception-V3 | 89.18 | 98.67 | 89.00 | 89.00 | 89.00 | |
MobileNet-V2 | 89.86 | 98.33 | 90.00 | 89.00 | 89.00 | |
Potato | ResNet-50 | 94.32 | 99.03 | 94.00 | 94.00 | 94.00 |
Xception | 96.18 | 99.42 | 96.00 | 96.00 | 96.00 | |
Inception-V3 | 96.05 | 99.64 | 96.00 | 96.00 | 96.00 | |
MobileNet-V2 | 92.59 | 98.68 | 93.00 | 93.00 | 93.00 | |
PlantDoc | ResNet-50 | 84.11 | 98.02 | 85.00 | 84.00 | 84.00 |
Xception | 84.30 | 98.10 | 85.00 | 84.00 | 84.00 | |
Inception-V3 | 81.00 | 98.05 | 81.00 | 81.00 | 81.00 | |
MobileNet-V2 | 80.81 | 97.86 | 81.00 | 81.00 | 81.00 | |
BreakHis 40\(\times \) | ResNet-50 | 95.50 | 99.00 | 95.00 | 95.00 | 95.00 |
Xception | 94.83 | 99.00 | 95.00 | 95.00 | 95.00 | |
Inception-V3 | 95.00 | 99.00 | 95.00 | 95.00 | 95.00 | |
MobileNet-V2 | 94.00 | 99.00 | 94.00 | 94.00 | 94.00 | |
BreakHis 100\(\times \) | ResNet-50 | 96.79 | 99.00 | 97.00 | 97.00 | 97.00 |
Xception | 95.19 | 99.00 | 95.00 | 94.00 | 94.00 | |
Inception-V3 | 95.67 | 99.00 | 96.00 | 96.00 | 96.00 | |
MobileNet-V2 | 95.83 | 99.00 | 96.00 | 96.00 | 96.00 | |
SIPaKMeD | ResNet-50 | 99.18 | 100.00 | 99.00 | 99.00 | 99.00 |
Xception | 98.98 | 100.00 | 99.00 | 99.00 | 99.00 | |
Inception-V3 | 98.37 | 100.00 | 98.00 | 98.00 | 98.00 | |
MobileNet-V2 | 98.17 | 100.00 | 98.00 | 98.00 | 98.00 |
