Emanuele Frontoni

TL;DR: The article surveys the state-of-the-art in augmented-, virtual-, and mixed-reality systems as a whole and from a cultural heritage perspective and identifies specific application areas in digital cultural heritage and makes suggestions as to which technology is most appropriate in each case.

TL;DR: Results show the appropriateness of the vision-based approach, which is robust to occlusions and light variations, and two algorithms for safe landing area detection, based on a feature optical flow analysis.

TL;DR: A Machine Learning architecture for Predictive Maintenance, based on Random Forest approach was tested on a real industry example, and preliminary results show a proper behavior of the approach on predicting different machine states with high accuracy.

TL;DR: In this article, a comparative analysis of different methods for automated building detection in aerial images and laser data at different spatial resolutions is presented, based on error measures obtained by superimposing the results on a manually generated reference map of each area.

TL;DR: Experimental results performed on the Center for Advanced Studies in Adaptive Systems datasets show that the proposed LSTM-based approaches outperform existing DL and ML methods, giving superior results compared to the existing literature.