Retinal disease classification through deep learning

The objective of this project is to develop an automated system capable of accurately detecting and classifying retinal diseases, including Age-related Macular Degeneration (AMD), Diabetic Retinopathy, Glaucoma, and normal retinal conditions. By leveraging deep learning algorithms such as CNN, MobileNet, ResNet, EfficientNet, and DenseNet, the project aims to create a robust classification model that can assist healthcare professionals in early diagnosis. The primary goal is to enhance the detection process by providing a real-time, accurate, and scalable solution for identifying retinal diseases using retinal images, which can be applied in clinical settings for early intervention, reducing the risks of vision loss and improving patient care