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N. Giulietti
Researcher at Marche Polytechnic University
Publications - 12
Citations - 33
N. Giulietti is an academic researcher from Marche Polytechnic University. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 1, co-authored 2 publications receiving 7 citations.
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Journal ArticleDOI
Performance of concretes manufactured with newly developed low-clinker cements exposed to water and chlorides: Characterization by means of electrical impedance measurements
Gloria Cosoli,Alessandra Mobili,N. Giulietti,Paolo Chiariotti,Giuseppe Pandarese,Francesca Tittarelli,Francesca Tittarelli,Tiziano Bellezze,N. Mikanovic,Gian Marco Revel +9 more
TL;DR: In this paper, the electrical impedance of three different concrete mixes during accelerated degradation tests is discussed. And the two new low-clinker cements adopted seem to improve the measurement sensitivity towards contaminants ingress with respect to the commercial one.
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Effect of Gasification Char and Recycled Carbon Fibres on the Electrical Impedance of Concrete Exposed to Accelerated Degradation
Alessandra Mobili,Gloria Cosoli,N. Giulietti,Paolo Chiariotti,Giuseppe Pandarese,Tiziano Bellezze,Gian Marco Revel,Francesca Tittarelli +7 more
TL;DR: In this article , the effect of carbon-based conductive recycled additions, i.e., recycled carbon fibres (RCF) and gasification char (GCH), on the mechanical, electrical, and durability properties of concretes was evaluated.
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SwimmerNET: Underwater 2D Swimmer Pose Estimation Exploiting Fully Convolutional Neural Networks
TL;DR: In this article , a new markerless 2D swimmer pose estimation approach based on the combined use of computer vision algorithms and fully convolutional neural networks is proposed, which is able to estimate the pose of a swimmer during exercise while guaranteeing adequate measurement accuracy.
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Correction of Substrate Spectral Distortion in Hyper-Spectral Imaging by Neural Network for Blood Stain Characterization
TL;DR: In this article , a neural network-based approach was proposed to detect whether a stain is blood or not and then obtain the spectra that the same stain would have on a reference white substrate with a mean absolute percentage error of 1.11%.
Journal ArticleDOI
Automated measurement system for detecting carbonation depth: Image-processing based technique applied to concrete sprayed with phenolphthalein
N. Giulietti,Paolo Chiariotti,Gloria Cosoli,Alessandra Mobili,Giuseppe Pandarese,Francesca Tittarelli,Francesca Tittarelli,Gian Marco Revel +7 more
TL;DR: An automated measurement system for detecting carbonation depth in concrete sprayed with phenolphthalein is discussed, which proves that the highest source of uncertainty is the measurement system, which, on the other hand, is robust to changes in the operator performing the measurement.