A hybrid deep learning framework for automated diabetic retinopathy detection combining EfficientNetB0 with Swin Transformer attention mechanisms. Features Bayesian uncertainty quantification through Monte Carlo Dropout, explainable AI visualizations with Grad-CAM, and specialized preprocessing techniques.
deep-learning bayesian-inference pre-processing monte-carlo-dropout efficientnet grad-cam-visualization swim-transformer explianable-ai
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Updated
Jul 31, 2025 - Python