Diabetic Retinopathy Detection Using Deep Learning
Abstract & Details
Research Area
Computer Science Engineering
Keywords
Diabetic Retinopathy
Deep Learning
Retinal Fundus Images
Convolutional Neural Networks (CNN)
Automated Diagnosis
Medical Image Analysis
Early Detection
Computer-Aided Diagnosis (CAD)
Abstract
Diabetic retinopathy (DR) is a leading cause of vision impairment, resulting from prolonged diabetes. Early detection is crucial to prevent irreversible damage, but manual diagnosis by ophthalmologists is time-consuming and prone to human error. This project proposes an automated approach for DR detection using deep learning, specifically the ResNet50 model, to classify retinal fundus images into different stages of diabetic retinopathy. The model was trained on a publicly available dataset such as Kaggle’s APTOS, leveraging transfer learning to enhance accuracy. Preprocessing techniques, including image augmentation and normalization, were applied to improve robustness. The ResNet50 architecture, known for its deep residual connections, effectively addressed vanishing gradient problems and improved feature extraction.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Sandesh Madhukar Shetake | D Y Patil Technical Campus, Talsande |
| 2 | Sushant Sanjay Varpe | D Y Patil Technical Campus, Talsande |
| 3 | Anurag Suresh Teurwade | D Y Patil Technical Campus, Talsande |
| 4 | Sameer Shivaji Patil | D Y Patil Technical Campus, Talsande |
How to Cite
Use the following formats to cite this article in your research.
APA Style
Shetake, Sandesh Madhukar, Varpe, Sushant Sanjay, Teurwade, Anurag Suresh, & Patil, Sameer Shivaji (2025). Diabetic Retinopathy Detection Using Deep Learning. International Journal of Advance Research and Innovative Ideas In Education, 11(2), 3026-3029.
MLA Style
Shetake, Sandesh Madhukar, et al. "Diabetic Retinopathy Detection Using Deep Learning." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, 2025, pp. 3026-3029.
IEEE Style
Sandesh Madhukar Shetake, Sushant Sanjay Varpe, Anurag Suresh Teurwade, and Sameer Shivaji Patil, "Diabetic Retinopathy Detection Using Deep Learning," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, pp. 3026-3029, 2025.
Vancouver Style
Shetake Sandesh Madhukar, Varpe Sushant Sanjay, Teurwade Anurag Suresh, Patil Sameer Shivaji. Diabetic Retinopathy Detection Using Deep Learning. International Journal of Advance Research and Innovative Ideas In Education. 2025;11(2):3026-3029.
Harvard Style
Shetake, Sandesh Madhukar, Varpe, Sushant Sanjay, Teurwade, Anurag Suresh, & Patil, Sameer Shivaji (2025) 'Diabetic Retinopathy Detection Using Deep Learning', International Journal of Advance Research and Innovative Ideas In Education, 11(2), pp. 3026-3029.
Chicago Style
Shetake, Sandesh Madhukar, et al. "Diabetic Retinopathy Detection Using Deep Learning." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 3026-3029.
Turabian Style
Shetake, Sandesh Madhukar, et al. "Diabetic Retinopathy Detection Using Deep Learning." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 3026-3029.
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