Image Classification on Tea leaf disease dataset (test)
99AccuracyDenseNet201
Evaluation results
| Method | Links | |
|---|---|---|
| DenseNet201Author=Proposed Model2026.04 | 99 | |
| YOLOv7Author=Soeb et al. [1]2026.04 | 97.3 | |
| MobileNetV2Author=Proposed Model2026.04 | 94 | |
| Inception3Author=Proposed Model2026.04 | 92 | |
| ShuffleNetAuthor=N. Yucel et al. [3]2026.04 | 91.3 | |
| Neural Network EnsembleAuthor=Karmokar et al. [9]2026.04 | 91 | |
| LeafNetAuthor=Chen et al. [2]2026.04 | 90.16 | |
| Ensemble modelAttention Module=CBAM block2025.12 | 85.68 | |
| XceptionAuthor=Ahammed et al. [4]2026.04 | 83.32 | |
| InceptionV3Attention Module=CBAM block2025.12 | 82.93 | |
| Ensemble modelAttention Module=SE block2025.12 | 82.07 | |
| InceptionV3Attention Module=SE block2025.12 | 80.46 | |
| Ensemble modelAttention Module=None2025.12 | 79.08 | |
| DenseNet201Attention Module=CBAM block2025.12 | 78.31 | |
| InceptionV3Attention Module=None2025.12 | 77.28 | |
| DenseNet201Attention Module=SE block2025.12 | 76.27 | |
| DenseNet201Attention Module=None2025.12 | 73.92 |