1. Detection of diabetic retinopathy using AlexNet and lenet CNN models.
- Author
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Vinayagam, Jananee, Murugan, Shanthalakshmi, Jesu, Sherine Glory, Vaidhya, Govindharajalu Kaliayaperumal, Narayanan, Nikghamanth Seshadri, and Thayil, Neya Babu
- Subjects
DIABETIC retinopathy ,CONVOLUTIONAL neural networks ,EYE diseases ,DIAGNOSIS - Abstract
Diabetic Retinopathy is a condition that is caused by excessive glycemia. It can often be tough to tell the variation among both DR and fundus photographs. To avoid difficulties, it is crucial to acknowledge. We can detect many Diabetic Eye Disease illnesses using CNNs. It also detects the colors and patterns of sores and matches them to relevant conditions during medical diagnosis, which is similar to human decision-making. The Django web framework showcases the output. To determine the most efficient and accurate categorization of Diagnosed images, researchers use many related images as input into convolutional semantic networks. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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