Efficient diabetic retinopathy diagnosis through U-Net – KNN integration in retinal fundus images
Author:
Affiliation:
1. AP / ECE Department, Government College of Engineering, Tirunelveli, India
2. AP / CSE, Anna University Regional Campus, Tirunelveli, India
Publisher
Informa UK Limited
Subject
General Computer Science,Control and Systems Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/00051144.2023.2251231
Reference45 articles.
1. Artificial intelligence for diabetic retinopathy
2. Diabetic retinopathy screening in the emerging era of artificial intelligence
3. Benzamin A Chakraborty C. Detection of hard exudates in retinal fundus images using deep learning. In 2018 Jt. 7th Int. Conf. Informatics Electron. Vis. 2nd Int. Conf. Imaging Vis. Pattern Recognition ICIEV-IVPR 2018; 2019. p. 465–469.
4. U-net Based Method for Automatic Hard Exudates Segmentation in Fundus Images Using Inception Module and Residual Connection
5. Artificial intelligence in diabetic retinopathy
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