Open AccessDetection of Eye Diseases using CNN
Author(s) -
Anas Farooqui,
Abdullah Bharde,
Ibrahim Ansari,
Farhana Siddiqui
Publication year - 2022
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-2486
Subject(s) - computer science , identification (biology) , artificial intelligence , glaucoma , convolutional neural network , image processing , diabetic retinopathy , deep learning , optometry , artificial neural network , machine learning , computer vision , medicine , image (mathematics) , ophthalmology , botany , biology , diabetes mellitus , endocrinology
For illness identification in medical pictures, image processing is important. These illness detection and classification techniques are unique to each human organ and picture type. It is possible to automate and/or aid doctors in clinical diagnosis by using image processing and machine learning methods. This article explains how to identify eye disorders using different image processing and machine learning methods. The suggested deep neural network model aids in the early detection of illnesses including Cataract, Diabetic Retinopathy, and Glaucoma. It may prompt people to seek the advice of an ophthalmologist for a screening. The suggested CNN model is simpler, more precise, and quicker.