Table 4 Evaluation results of 9 models on soybean disease dataset.
From: A hypergraph cell membrane computing network model for soybean disease identification
Models | Classification accuracy (%) | Precision (%) | Recall (%) | Specificity (%) | F1 score (%) |
|---|---|---|---|---|---|
AlexNet | 89.00 | 89.13 | 87.23 | 90.57 | 88.17 |
LeNet5 | 91.00 | 97.50 | 82.98 | 98.11 | 89.66 |
Vgg16 | 88.00 | 84.31 | 91.49 | 84.91 | 87.76 |
EfficientNetB0 | 95.00 | 100 | 89.36 | 100 | 94.38 |
InceptionV3 | 95.00 | 92.00 | 97.87 | 92.45 | 94.85 |
DenseNet121 | 64.00 | 56.79 | 97.87 | 33.96 | 71.88 |
ResNet50 | 95.00 | 95.65 | 93.62 | 96.23 | 94.62 |
ResNet101 | 89.00 | 89.13 | 87.23 | 90.57 | 88.17 |
HcmcNet | 98.00 | 97.87 | 97.87 | 98.11 | 97.87 |
