Abstract– Diabetic eye disease is a complexity that affects people having diabetes for a longer time. By affecting the blood vessels it can cause blurry vision or even blindness to the patients. Thus, detecting the eye disease at an early stage can help many of the diabetic patients to get the required treatment and intern increases the survival rate. In the proposed system, the CNN algorithm of machine learning is used to detect the diabetic eye diseased by either using the thermal images. These images are pre-processed by converting them from RGB to GRAY based on which the required features are extracted. To detect the diabetic retinopathy, here the Convolution Neural Network is used to classify 5 stages of the diseased eye.

PDF | DOI: 10.17148/IJARCCE.2023.12603

Open chat
Chat with IJARCCE