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Maurizio Lualdi

Researcher at Polytechnic University of Milan

Publications -  55
Citations -  698

Maurizio Lualdi is an academic researcher from Polytechnic University of Milan. The author has contributed to research in topics: Ground-penetrating radar & Radar. The author has an hindex of 13, co-authored 53 publications receiving 530 citations. Previous affiliations of Maurizio Lualdi include Instituto Politécnico Nacional.

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Landmine detection from GPR data using convolutional neural networks

TL;DR: A pipeline for buried landmine detection based on convolutional neural networks applied to ground-penetrating radar (GPR) images is proposed, capable of recognizing whether a B-scan profile obtained from GPR acquisitions contains traces of buried mines.
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The use of georadar to assess damage to a masonry Bell Tower in Cremona, Italy

TL;DR: In this article, the application of georadar to the detection of three main structural problems for the Bell Tower (Torrazzo) of Cremona is presented, together with the difficulties in acquisition and data elaboration and the description of auxiliary investigations used to validate interpretation of the results.
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Seismic microzoning map: approaches, results and applications after the 2016–2017 Central Italy seismic sequence

TL;DR: In this article, the authors presented the results and critical issues of the above-mentioned steps of the seismic microzonation of level 3 (SM3) procedure, together with some remarks on the use of SM3 output in supporting seismic design for reconstruction.
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Landmine Detection Using Autoencoders on Multipolarization GPR Volumetric Data

TL;DR: In this article, a specific kind of convolutional neural network (CNN) known as autoencoder was used to analyze volumetric data acquired with ground penetrating radar (GPR) using different polarizations.
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Non-Destructive Testing Techniques Applied for Diagnostic Investigation: Syracuse Cathedral in Sicily, Italy

TL;DR: In this article, an accurate geometric survey of the surface problems and defects allowed the localization of the most damaged area, suggesting the need for further control by non-destructive testing (NDT).