Diabetic Retinopathy Detection using Deep Learning Techniques

This paper was published while collaborating the faculties of the Department of Computer Science. The contribution was significant especially in the development of deep learning models using Python as the programming language and Tensorflow as the deep-learning framework.

Digital fundus images of the eye were used to classify Diabetic Retinopathy in the adults. Various configurations of CNN (architecture, optimiser, activation function) were tried to find the best performing configuration.

The results were published in the Journal of Computer Science which can found in https://doi.org/10.3844/jcssp.2020.305.313