Identification of Diabetic Retinopathy

Identification Of Diabetic Retinopathy Using CNN, develops an automatic method for detecting diabetic retinopathy (DR) using Convolutional Neural Networks (CNNs). Diabetic retinopathy is a severe eye disease leading to blindness in diabetic patients, necessitating early and accurate detection for effective treatment. The system employs a CNN to identify retinal blood vessels affected by DR, removing noise pixels for enhanced accuracy. Achieving a training accuracy of 88.3% and a testing accuracy of 75%, the project provides a valuable tool for ophthalmologists to diagnose and treat DR promptly, improving patient outcomes.