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This project focuses on detecting glaucoma using deep learning models trained on fundus images. It includes data preprocessing, supervised learning with ResNet50, self-supervised learning using Masked Autoencoders (MAE), and domain adaptation techniques to improve model generalization across different datasets.
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dmdaksh/glaucoma_classification
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This project focuses on detecting glaucoma using deep learning models trained on fundus images. It includes data preprocessing, supervised learning with ResNet50, self-supervised learning using Masked Autoencoders (MAE), and domain adaptation techniques to improve model generalization across different datasets.
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