About this document
DR DETECTION Miniproject Fixed by sastikadeepika is a document available to read on EtoBox.
This project report presents an automated system for detecting and classifying Diabetic Retinopathy (DR) from fundus images using a fine-tuned ResNet-50 deep learning model. The system achieves 87.9% accuracy and an AUC-ROC of 0.962, aiming to enhance early DR screening in resource-limited settings while addressing challenges in manual grading and accessibility. The report outlines the project
- Author
- sastikadeepika
- Language
- EN