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. 2020 Oct 1;138(11):1213–1215. doi: 10.1001/jamaophthalmol.2020.3442

Table. Classification Accuracy of the Conventional Deep Learning Models on Adversarial Examples Crafted by the Fast Gradient Sign Method (FGSM) Using InceptionV3.

Model Accuracy of deep learning models, %a
InceptionV3 MobileNetV2 ResNet50
Fundus photography
No attack 89.1 88.6 89.9
FGSM using the InceptionV3 modela 13.4 63.7 77.5
Ultrawide-field fundus photography
No attack 97.6 97.4 96.8
FGSM using the InceptionV3 modelb 5.0 74.3 72.1
Optical coherence tomography
No attack 99.6 99.5 99.6
FGSM using the InceptionV3 modelb 8.2 68.8 64.8
a

The results were derived from the validation dataset.

b

Perturbation coefficient ε = 0.010.