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Found 2 papers, 1 papers with code
Uncertainty Quantified Deep Learning for Predicting Dice Coefficient of Digital Histopathology Image Segmentation
Results from this study suggest that linear models can learn coefficients of uncertainty quantified deep learning and correlations ((Spearman's correlation (p<0. 05)) to predict Dice scores of specific regions of medical images.
Gradient Descent: The Ultimate Optimizer
This allows us to easily apply the method to other optimizers and hyperparameters (e. g. momentum coefficients).
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