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About Diabetic Retinopathy Detection Using Deep Learning
This document discusses using deep learning techniques to detect diabetic retinopathy (DR) from fundus eye images. DR damages the retina and can lead to vision loss if not detected early. The authors trained a DenseNet model on a dataset of over 3,600 fundus images to classify images into the 5 stages of DR. They achieved a high accuracy of 96.11% using this model. They also compared the performance of DenseNet to VGG16 on this task. Detecting DR early using deep learning can help doctors provide timely treatment to prevent vision loss.
Detailed Information
| Author: | ['Shreyas S R'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 6 |
| Language: | English |
| Format: | |
| Price: | FREE |
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