Table 6 Performance Comparison.
From: Advancing plant leaf disease detection integrating machine learning and deep learning
Sl. No | Reference | Approach | Accuracy |
|---|---|---|---|
1 | Hierarchical SVM classification (Citrus Leaf disease dataset) | 91.76% | |
2 | CNN with TGVFCMS (Alliance of Bioversity International and CIAT Banana Image Library dataset) | 93.45% | |
3 | Deeper lightweight convolutional neural network architecture (DLMC-Net) (PlantVillage dataset) | 93.56% | |
4 | Rehearsal-based class-incremental learning approaches (PlantVillage dataset) | 66.60% | |
5 | Proposed Method | Inception v3 with SVM (Banana dataset) VGG19 with kNN (Custard Apple Leaf and Fruit dataset) VGG19 with kNN (Fig Leaf dataset) Inception v3 with SVM (Potato Leaf dataset) | 91.9% 99.1% 86.5% 62.6% |
