Detail

Training and Validation Dataset of MgAl2O4 SEM Fracture Images for "Toward Quantitative Fractography Using Convolutional Neural Networks"

Tsopanidis, Stylianos; Osovski, Shmuel

Description

This is a dataset of SEM fracture images for training and validation of deep learning algorithms. The fracture surfaces of the MgAl2O4 ceramic material can be used to train a convolutional neural network for identifying the intergranular and transgranular fracture modes. European Union's Horizon2020 Programme (Excellent Science, Marie-Sklodowska-Curie Actions) under REA grant agreement 675602 (Project OUTCOME) Contact: Stylianos Tsopanidis <[email protected]> or Shmuel Osovski <[email protected]>