Diabetic retinopathy (DR) produces bleeding, exudation, and new blood vessel formation conditions. DR can damage the
retinal blood vessels and cause vision loss or even blindness. If DR is detected early, ophthalmologists can use lasers to create tiny
burns around the retinal tears to inhibit bleeding and prevent the formation of new blood vessels, in order to prevent deterioration of
the disease. The rapid improvement of deep learning has made image recognition an effective technology; it can avoid misjudgments
caused by different doctors’ evaluations and help doctors to predict the condition quickly. The aim of this paper is to adopt visualization
and preprocessing in the ResNet-50 model to improve module calibration, to enable the model to predict DR accurately.
Keyword : Deep Learning, ResNet – 50 , Visualization