Eye-diseases-classification and ocular-disease-classification

These are **competitors**: both implement multiclass CNN-based classification of ocular diseases from fundus/retinal images, targeting the same use case with overlapping functionality and no technical interdependence.

Maintenance 0/25
Adoption 3/25
Maturity 16/25
Community 15/25
Maintenance 6/25
Adoption 5/25
Maturity 8/25
Community 15/25
Stars: 4
Forks: 4
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 9
Forks: 4
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stale 6m No Package No Dependents
No License No Package No Dependents

About Eye-diseases-classification

somaiaahmed/Eye-diseases-classification

The Eye Disease Classification project aims to develop a robust model for the automated classification of retinal images . Leveraging a diverse dataset sourced from reputable repositories, the project employs a Convolutional Neural Network (CNN) architecture, with a focus on utilizing the pre-trained VGG19 model.

About ocular-disease-classification

YgLK/ocular-disease-classification

Multiclass classification of eye diseases based on eye fundus images using CNNs

This project helps ophthalmologists and optometrists quickly screen for common eye diseases. It takes a fundus image of a patient's eye and classifies it as 'Normal,' 'Cataract,' or 'Myopia,' providing a rapid initial assessment. It is designed for eye care professionals or medical technicians who need to analyze eye scans efficiently.

ophthalmology optometry disease-screening medical-imaging diagnostic-support

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