This project involves building a Glaucoma Detection AI-ML model using a Convolutional Neural Network (CNN) to classify retinal images as either "Glaucoma Affected" or "Normal." The model is trained using ImageDataGenerator for data augmentation, with binary cross-entropy loss, Adam optimizer, and is saved in `.keras` format.

Using CNNs to classify an image into normal or glaucomatous, using retinal fundus images by transfer learning.

Detect glaucoma early with our app!

Actively maintained and comprehensive public glaucoma dataset catalog

Comparing MobileNet and EfficientNet on Glaucoma Detection

Glaucoma prediction system

Code for Princeton ORFE Senior Thesis (Domain Generalization for Deep Learning-Based Glaucoma Classification)

Deep learning project for ocular eye disease classification

Glaucoma detection using deep learning(cnn)

Glaucoma Detection based on Optic Cup and Disc Segmentation using U-Net

This project uses deep learning algorithms and the Keras library to determine if a person has certain diseases or not from their chest x-rays and other scans. The trained model is displayed using Streamlit, which enables the user to upload an image and receive instant feedback.

Standardized Multi-Channel Dataset for Glaucoma (SMDG-19) is a collection and standardization of 19 public full-fundus glaucoma images and associated metadata.

IBM Advanced Data Science project

Automated diagnosis of glaucoma using machine learning

Glaucoma and Non-Glaucoma classification using ML/Dl and ensemble approaches using Image Feature Extraction Using HOG (Histogram of Gradient)

In this paper, we developed a machine learning model ensemble approach consisting of a support vector machine (SVM), random forest (RF), Multilayer Perceptron (MLP), and Majority-VotingEnsemble classifiers.

General assembly DSIF5 Singapore Capstone project 22-Oct-2022

Glaucoma detection transfer learning model designed with EfficientNet

Evaluation of a simple CNN model for glaucoma detection trained on a single public dataset against complex architectures trained on multiple public/private datasets

Source code for GARDNet: Robust Multi-View Network for Glaucoma Classification in Color Fundus Images