Luca Zacheo
Deep Learning for automatic crack detection inside tunnels - Second Prototype.
Rel. Roberto Garello, Marina Mondin. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2019
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Abstract
The rapid urbanization of cities around the globe and the corresponding exponential growth in transportation infrastructure to support ever increasing population densities, has led to the corresponding increase in road tunnels as a means of alleviating congestion, where and when possible. This necessitates development of automated techniques for detection of cracks on the surfaces inside tunnels given the high costs of manual visual inspection both monetarily and in terms of time. Structural integrity testing of the road tunnels imposes the first problem of managing the traffic flow during the inspections, since it may not always be possible to block the traffic and examine the entire tunnel to perform a human visual inspection or to prepare and mount a complex robotic structure for the same purpose.
In this scenario, a low-cost automatic system can be a smart solution and can overcome many of the previously described problems
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