IDENTIFICAZIONE DELLA GEOMETRIA DELLA ROTAIA ATTRAVERSO UN APPROCCIO DEEP LEARNING

This thesis work provides a different approach, based on a deep learning strategy, to improve the rail classification of profiles collected along a track, that presents two rail types which have a very similar shape and are often misclassified. A convolutional neural network, therefore, has been trained to perform the rail classification task, ensuring higher performances.