Marco Giglio

According to our database, Marco Giglio authored at least 10 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Mitigating the Impact of Temperature Variations on Ultrasonic Guided Wave-Based Structural Health Monitoring through Variational Autoencoders.

Rafael Junges, Luca Lomazzi, Lorenzo Miele, Marco Giglio, Francesco Cadini

Sensors, March, 2024

Physics-Informed Neural Networks for the Condition Monitoring of Rotating Shafts.

Marc Parziale, Luca Lomazzi, Marco Giglio, Francesco Cadini

Sensors, 2024

2023

Towards a deep learning-based unified approach for structural damage detection, localisation and quantification.

Luca Lomazzi, Marco Giglio, Francesco Cadini

Eng. Appl. Artif. Intell., May, 2023

Towards Automatic Crack Size Estimation with iFEM for Structural Health Monitoring.

Daniele Oboe, Dario Poloni, Claudio Sbarufatti, Marco Giglio

Sensors, April, 2023

Variable Thickness Strain Pre-Extrapolation for the Inverse Finite Element Method.

Dario Poloni, Daniele Oboe, Claudio Sbarufatti, Marco Giglio

Sensors, February, 2023

2022

A Fuzzy-set-based Joint Distribution Adaptation Method for Regression and its Application to Online Damage Quantification for Structural Digital Twin.

Xuan Zhou, Claudio Sbarufatti, Marco Giglio, Leiting Dong

CoRR, 2022

2021

Shape Sensing of a Complex Aeronautical Structure with Inverse Finite Element Method.

Daniele Oboe, Luca Colombo, Claudio Sbarufatti, Marco Giglio

Sensors, 2021

2020

On the Evaluation of a Coupled Sequential Approach for Rotorcraft Landing Simulation.

Demetrio Cristiani, Luca Colombo, Wojciech Zielinski, Claudio Sbarufatti, Francesco Cadini, Michal Dziendzikowski, Marco Giglio

Sensors, 2020

2019

Robust Identification of Strain Waves due to Low-Velocity Impact with Different Impactor Stiffness.

Alessio Beligni, Claudio Sbarufatti, Andrea Gilioli, Francesco Cadini, Marco Giglio

Sensors, 2019

2015

Real-Time Prognosis of Crack Growth Evolution Using Sequential Monte Carlo Methods and Statistical Model Parameters.

Matteo Corbetta, Claudio Sbarufatti, Andrea Manes, Marco Giglio

IEEE Trans. Reliab., 2015