Research Article
Automatic Detection of AMD and DME Retinal Pathologies Using Deep Learning
Table 5
Obtained results on local dataset.
| Model | Accuracy | Precision | Recall | score |
| Fine-tuning of Xception | 96.77% | 96.66% | 97% | 97% | Features extraction from “sepconv2_bn”+CNN | 98% | 94.66% | 94.66% | 94.66% | BCNN (Xception, Xception) | 98.56% | 96.33% | 96.66% | 95% | Fine-tuning de Inception-resnet-v2 | 96.11% | 95% | 95% | 95% | Features extraction from “block8_1_ac”+CNN | 97.12% | 98.33% | 98% | 98% | BCNN (Inception-ResnetV2, Inception-ResnetV2) | 96.44% | 98.66% | 99% | 98.33% | The from scratch “OCTorch-Net” | 97.65% | 96% | 95.6% | 95.8% |
|
|