Diabetic retinopathy ... using techniques like Contrast Limited Adaptive Histogram Equalization (CLAHE), noise reduction, and cropping to enhance feature extraction and improve model performance. A ...

[2] Arkadiusz Kwasigroch, Bartlomiej Jarzembinski and Michal Grochowski, Deep CNN based decision support ... Diagnosis of Diabetic Retinopathy Using Machine Learning Classification Algorithm’, IEEE ...

The power of deep learning is being unleashed by using it widely ... in the form of CNN we implemented, exhibited notable performance resulting in 87.38% accuracy and around 1% loss. We made this ...

Abstract: Deep learning has been proposed as one of the automated solutions for diabetic retinopathy (DR) severity classification problem. However, most of the successful deep learning models are ...