Classification of Diabetic Retinopathy Stages Using Deep Learning.

Date of Submission

December 2018

Date of Award

Winter 12-12-2019

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science


Machine Intelligence Unit (MIU-Kolkata)


Mitra, Sushmita (MIU-Kolkata; ISI)

Abstract (Summary of the Work)

Diabetic Retinopathy (DR) is the leading cause of blindness in the working-age population of the developed world and is estimated to affect over 93 million people.Detecting DR is a time-consuming and manual process that requires a trained clinician to examine and evaluate digital color fundus photographs of the retina.In this report, we have proposed three different methods for classifying DR Images. The first method uses Convolutional Neural Network. The Second method uses a pre-trained 2D VGG16 ConvNet model for feature extraction. The third method uses Capsule Network. We discuss merits and demerits of each method.


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Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


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