Fig. 6: Naturally inspired dataset for convolutional neural network models training.
From: Structural integrity of aging steel bridges by 3D laser scanning and convolutional neural networks
a Data generation is based on real data from three decommissioned girders. b Thickness contour maps are generated for each beam end, and c several multivariable Gaussian distributions are fitted to analytically describe the section loss profiles. d 1421 naturally inspired corrosion scenarios are generated by parametrizing the distributions locations and their covariance values. Both lengths and thickness are normalized, so no units are illustrated.
