Segmentation Notes

Loss functions for image segmentation, Link1

Loss Functions in Segmentation

Image segmentation can be thought of a classification task on the pixel level, and the choice of loss function for the task of segmentation is key in determining both the speed at which a Machine-Learning model converges, as well to some extent, the accuracy of the model.

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Dice loss. This loss is obtained by calculating smooth dice coefficient function. This loss is the most commonly used loss is segmentation problems.

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