Table 3.
Scenarios of performance for medicinal plant identification based on findings from some recent studies.
| Dataset | Model | Accuracy | Reference |
|---|---|---|---|
| VNPLANT-200 DATASET | VGG16 | 76 % | [21] |
| InceptionV3 | 82.50 % | ||
| MobileNetV2 | 87.92 % | ||
| Xception | 88.26 % | ||
| Densenet121 | 88 % | ||
| Morocco AMPs | ResNet50 | 90 % | [45] |
| Dynamic CNN | 97 % | ||
| Iran dataset | CNN | 97.6 % | [37] |
| AyurLeaf | CNN | 95 % | [36] |
| SVM | 96.7 % | ||
| Bangladeshi medicinal plant dataset | CNN | 71 % | [46] |
| PlantCLEF 2015 | EfficientNet-B1 | 87 % | [24] |
| Private dataset | Ayur-PlantNet | 92.7 % | [29] |