Deep Diabetic And Identification System Of Diabetic Eye Diseases Using Deep Neural Networks

Abstract

Diabetic retinopathy (DR) is a leading cause of vision impairment among diabetic patients. Early detection and timely treatment are crucial to prevent irreversible vision loss. This project introduces a comprehensive system leveraging deep neural networks, specifically Convolutional Neural Networks (CNNs), for the automated detection of diabetic eye diseases. The system comprises two primary modules: Admin and User. The Admin module facilitates dataset management, preprocessing, and model training, while the User module allows individuals to upload retinal images and receive diagnostic results. By integrating advanced deep learning techniques with user-friendly interfaces, this system aims to enhance the accuracy and efficiency of DR detection, thereby supporting healthcare professionals in early diagnosis and treatment planning.