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glaucoma-detector

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Glaucoma detection automation project. Trained a binary image classifier using CNNs and deployed as a streamlit web app. It takes eye (retinal scan) image as input and outputs whether the person is affected by glaucoma or not.

  • Updated Oct 6, 2021
  • Python

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.

  • Updated Oct 6, 2024
  • Jupyter Notebook

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