ECCOMAS 2022

9/6/22    11:00 - 13:00
Advances in SHM guided by artificial intelligence and data fusion I  
Minisymposium organized by ILARIA VENANZI, FILIPPO UBERTINI and SIMON LAFLAMME
Room: Nordland (GF)
MS102A
Chair: Ilaria Venanzi
CoChair: Noemi Friedman
Advanced deep learning comparisons for non-invasive tunnel lining assessment from ground penetrating radar profiles
Marco Martino Rosso, Giulia Marasco, Leonardo Tanzi, Salvatore Aiello, Angelo Aloisio, Raffaele Cucuzza, Bernardino Chiaia, Giansalvo Cirrincione and Giuseppe Carlo Marano

Classification of compromised DOFS data with LSTM neural networks
Valeria Usenco and Kaspar Lasn

Machine learning for explainability of structural health monitoring data of a viaduct
Noemi Friedman, Zeynep Tasci, Uros Bohinc and Jan Kalinc

Deep neural networks for unsupervised damage detection on the Z24 bridge
Valentina Giglioni, Ilaria Venanzi, Valentina Poggioni, Alina Elena Baia, Alfredo Milani and Filippo Ubertini

Enabling supervised learning in structural health monitoring by simulating damaged structure responses through physics based models
Luca Rosafalco, Andrea Manzoni, Stefano Mariani and Alberto Corigliano