rsk97/Diabetic-Retinopathy-Detection
DIAGNOSIS OF DIABETIC RETINOPATHY FROM FUNDUS IMAGES USING SVM, KNN, and attention-based CNN models with GradCam score for interpretability,
The project implements a multi-model ensemble combining traditional ML (SVM, KNN) with attention-based CNN architectures, leveraging GradCAM visualization to highlight clinically relevant retinal regions for explainability. Built around fundus image preprocessing and feature extraction pipelines, it bridges classical and deep learning approaches to improve diagnostic confidence across different model families. Selected for Google AI ML Mentorship Bootcamp recognition.
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MIT
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Last pushed
Sep 02, 2023
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