Image Classification on The Eye Disease Image Dataset (test)
98.54AUCProposed Model
Evaluation results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| Proposed Model2025.05 | 98.54 | 97.99 | 0.071 | 98.19 | 93.22 | 100 | |
| DeiT-xLoRA=false2025.05 | 98.53 | 87.01 | 0.411 | 88.07 | 81.58 | 100 | |
| ViT2025.05 | 97.97 | 80.12 | 0.4976 | 86.75 | 77.21 | 99.64 | |
| Swin Transformer2025.05 | 97.92 | 84.87 | 0.4959 | 85.98 | 83.35 | 99.09 | |
| DeiTMultiscale Path Embedding=false2025.05 | 97.2 | 80.96 | 0.5159 | 85.71 | 79.52 | 100 | |
| Efficient Former2025.05 | 96.96 | 84.37 | 0.5481 | 88.98 | 81.33 | 98.68 | |
| DINOv22025.05 | 96.93 | 79.46 | 0.6032 | 83.12 | 73.98 | 95.38 | |
| ViTMAE2025.05 | 88.5 | 52.99 | 1.2562 | 83.48 | 23.78 | 72.58 | |
| SegFormer2025.05 | 86.73 | 52.54 | 1.2413 | 60.63 | 28.79 | 99.2 | |
| ConvNeXt V22025.05 | 84.75 | 51.52 | 1.3506 | 57.19 | 28.95 | 75.63 | |
| RegNet2025.05 | 84.25 | 51.2 | 1.399 | 64.27 | 16.4 | 98.08 | |
| CvT2025.05 | 77.95 | 41.05 | 1.584 | 49.95 | 11.38 | 95.41 |