| Autor: |
Sudha, S., Srinivasan, A., Devi, T. Gayathri, Muruganandam, N. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 3180 Issue 1, p1-7, 7p |
| Abstrakt: |
Diabetic Retinopathy (DR) is a medical condition that arises when there is leakage of blood and other fluids from the tiny retinal blood vessels. If it is left untreated, eye blindness will occur. Diabetic retinopathy has two stages: early stage or Non-Proliferative DR (NPDR), advanced stage or Proliferative DR (PDR). The proposed system detects diabetic retinopathy using Xception algorithm. It classifies early stage of diabetic retinopathy into mild, moderate and severe. So the four categories of detections are mild, moderate, severe and proliferative stage. Fundus images from the datasets are pre-processed to convert image size to 299 299. The deep convolutional neural network utilizes 70% of the images during training phase and 30% in the testing phase. The overall detection accuracy is 97.94% [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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