Deep Learning-Based Ocular Disease Recognition

This study investigates the use of image classification methods to identify eye disorders using fundus images. Ocular can significantly affect a person's quality life, but frequent exams help them early and prevent vision loss. Manual diagnosis, however, take while is prone mistakes made by humans. suggests utilising deep learning automatically from photos. To classify several disorders, such as age-related macular degeneration, cataracts, glaucoma, convolutional neural network (CNN) model created trained sizable dataset The proposed CNN achieves high accuracy in ocular diseases, demonstrating potential automated diagnosis for detection prevention results this research indicate that techniques improve speed disease recognition, paving way improved health management.