Figure 4
Segmentation error and model confidence. Core images (A–F), ground truth segmentation masks (B–G), model predictions (C–H), model confidence (D–I), and segmentation error (E–L) are shown for two validation and test representative cores. The model confidence represents the prediction probability associated with the predicted class. The segmentation error is the normalized categorical cross-entropy calculated between the prediction and the ground truth.
