Analysis of Railway Track Irregularities with Convolutional Autoencoders and Clustering Algorithms
Using Predictive Uncertainty for Cleaning Noisy Annotations
Impact of Training Set Size on the Ability of Deep Neural Networks to Deal with Omission Noise