On damage monitoring in historical buildings via Neural Networks
Leonarda Carnimeo, Dora Foti, Vitantonio Vacca · 2015
It is well known that ancient buildings suffer a high vulnerability to hazards, which may induce unpredictable damages. For this purpose, a main objective to be pursued concerns with the development of techniques for monitoring historical buildings and immediately alerting in case of early vulnerability warnings. This paper proposes a noninvasive Neural Network-based (NN-based) approach for Monitoring heritage buildings providing alerts in risk events. More in detail, a neural approach is suggested with the aim of predicting early warnings of risk events by detecting time novelties in images of historical evidences.