Deep Learning for Detection and Severity Classification of Diabetic Retinopathy

The objective of this project is to automate the detection of Diabetic Retinopathy and evaluate the severity with high efficiency, through an overall feasible approach. This project explores the use of various Convolutional Neural Network Architectures on images from the dataset after being subjected to appropriate image processing techniques like local average color subtraction to aid in highlighting the germane features from a fundoscopy, thereby augmenting the detection and evaluation process of Diabetic Retinopathy as well as serve as an expert guidance system for practitioners around the world.