Fig. 2: Schematics of the neural network structure.
From: A convolutional neural network for defect classification in Bragg coherent X-ray diffraction
The NN model consists of five convolution layers with Relu activation function. We use dropout46 in all layers with a dropout rate of 0.2, to avoid overfitting. The model ends with 2 fully connected layers with a last softmax activation function. The model takes the 3D 64 × 64 × 64 diffraction as input and predicts the probability for each class (defect-free, screw, edge).
