A U-net semantic segmentation model trained on MgAl2O4 fracture surfaces quantifies intergranular and transgranular modes in SEM images, with reported mean IoU of 91.1% on the training material and 94% on untrained Al2O3.
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Toward quantitative fractography using convolutional neural networks
A U-net semantic segmentation model trained on MgAl2O4 fracture surfaces quantifies intergranular and transgranular modes in SEM images, with reported mean IoU of 91.1% on the training material and 94% on untrained Al2O3.