Eye is the essential sense organ for vision function. Due to the fact that certain eye disorders might result in vision loss, it is essential to diagnose and treat eye diseases early on. By identifying common eye illnesses and performing an eye check, eye care providers can safeguard patients against vision loss or blindness. Convolutional neural networks (CNN) and transfer learning were employed in this study to discriminate between a normal eye and one with diabetic retinopathy, cataract, or glaucoma disease. Using transfer learning for multi-class classification, high accuracy was achieved at 94% while the traditional CNN achieved 84% rate.
@article{arxiv.2307.10501,
title = {Eye Disease Classification Using Deep Learning Techniques},
author = {Tareq Babaqi and Manar Jaradat and Ayse Erdem Yildirim and Saif H. Al-Nimer and Daehan Won},
journal= {arXiv preprint arXiv:2307.10501},
year = {2023}
}