@article {, title = {Machine Learning in Capital Markets: Decision Support System for Outcome Analysis}, journal = {IEEE Access}, volume = {8}, year = {2020}, pages = {109080-109091}, doi = {10.1109/ACCESS.2020.3001455}, author = {R. Rosati and L. Romeo and C. A. Goday and T. Menga and E. Frontoni} } @article {, title = {Measurement of Users{\textquoteright} Well-Being Through Domotic Sensors and Machine Learning Algorithms}, journal = {IEEE Sensors Journal}, volume = {20}, year = {2020}, pages = {8029-8038}, doi = {10.1109/JSEN.2020.2981209}, author = {S. Casaccia and L. Romeo and A. Calvaresi and N. Morresi and A. Monteri{\`u} and E. Frontoni and L. Scalise and G. M. Revel} } @article {paolanti2017modelling, title = {Modelling and Forecasting Customer Navigation in Intelligent Retail Environments}, journal = {Journal of Intelligent \& Robotic Systems}, year = {2017}, month = {10}, pages = {1{\textendash}16}, abstract = {

Understanding shopper behaviour is one of the keys to success for retailers. In particular, it is necessary that managers know which retail attributes are important to which shoppers and their main goal is to improve the consumer shopping experience. In this work, we present sCREEN (Consumer REtail ExperieNce), an intelligent mechatronic system for indoor navigation assistance in retail environments that minimizes the need for active tagging and does not require metrics maps. The tracking system is based on Ultra-wideband technology. The digital devices are installed in the shopping carts and baskets and sCREEN allows modelling and forecasting customer navigation in retail environments. This paper contributes the design of an intelligent mechatronic system with the use of a novel Hidden Markov Models (HMMs) for the representation of shoppers{\textquoteright} shelf/category attraction and usual retail scenarios such as product out of stock or changes on store layout. Observations are viewed as a perceived intelligent system performance. By forecasting consumers next shelf/category attraction, the system can present the item location information to the consumer, including a walking route map to a location of the product in the retail store, and/or the number of an aisle in which the product is located. Effective and efficient design processes for mechatronic systems are a prerequisite for competitiveness in an intelligent retail environment. Experiments are performed in a real retail environment that is a German supermarket, during business hours. A dataset, with consumers trajectories, timestamps and the corresponding ground truth for training as well as evaluating the HMM, have been built and made publicly available. The results in terms of Precision, Recall and F1-score demonstrate the effectiveness and suitability of our approach, with a precision value that exceeds the 76\% in all test cases.

}, issn = {0921-0296}, doi = {10.1007/s10846-017-0674-7}, url = {https://doi.org/10.1007/s10846-017-0674-7}, author = {Marina Paolanti and Daniele Liciotti and R. Pietrini and Adriano Mancini and Emanuele Frontoni} } @conference {Cenci:2017:MAP:3109761.3109773, title = {Movements Analysis of Preterm Infants by Using Depth Sensor}, booktitle = {Proceedings of the 1st International Conference on Internet of Things and Machine Learning}, series = {IML {\textquoteright}17}, year = {2017}, month = {10-2017}, pages = {12:1{\textendash}12:9}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, abstract = {

Qualitative assessment of general movements in preterm infants is widely used in clinical practice. It can enable early detection of neurological dysfunctions and consequent neuromotor impairments in high risk infants. However, the outcome of these assessments is not standardized and it is influenced by examiner{\textquoteright}s subjective interpretation. For this reason, there is an increasing interest in the use of automated movement recognition technologies being applied in this field. In this work, we use a video-based system for preterm infant{\textquoteright}s movements assessment to provide a 3D\ motion analysis method able to extract some important indicators from the sequence of depth images collected by using an RGB-D sensor placed over the infant lying on the crib. The advantage of the proposed method is that it is objective, contactless, non-invasive, easy to install, affordable and suitable to be used in an indoor environment with poor lighting, as might be rooms in the Neonatal Intensive Care Unit, where these infants are taken into care. Experimental results show that the proposed method is able to derive from statistical analysis of depth data some key performance indicators, each of which describes different characteristics of the infant{\textquoteright}s spontaneous movements. Preliminary tests are conducted in the experimental phase on a preterm infant hospitalized in a women{\textquoteright}s and children{\textquoteright}s hospital. The project can be used to investigate the relationship between the characteristics of spontaneous movements and the presence of pathologies as cerebral palsy or other minor neurological dysfunctions.

}, keywords = {3D tracking, clustering, modelling, preterm infant{\textquoteright}s movement analysis}, isbn = {978-1-4503-5243-7}, doi = {10.1145/3109761.3109773}, url = {http://doi.acm.org/10.1145/3109761.3109773}, author = {Annalisa Cenci and Daniele Liciotti and Emanuele Frontoni and Primo Zingaretti and Virgilio Paolo Carnielli} } @conference {mancini2016multi, title = {A multi/hyper-spectral imaging system for land use/land cover using unmanned aerial systems}, booktitle = {Unmanned Aircraft Systems (ICUAS), 2016 International Conference on}, year = {2016}, pages = {1148{\textendash}1155}, publisher = {IEEE}, organization = {IEEE}, author = {Adriano Mancini and Emanuele Frontoni and Primo Zingaretti} } @article {Fulvio2016273, title = {Multi-Point Stereovision System for Contactless Dimensional Measurements}, journal = {Journal of Intelligent and Robotic Systems: Theory and Applications}, volume = {81}, number = {2}, year = {2016}, note = {cited By 0}, pages = {273-284}, abstract = {

The paper focuses on the design of a fast and reliable multi-point vision-based measurement system able to be flexible, low cost and accurate for quality control in industrial robotics applications. The paper discusses a new method for integrating visual quality control in highly dynamic manufacturing lines, where products are added or removed from production. The structure of the vision-based measurement system is described. In particular, the stereo system is created by the movement of a single camera mounted on a six-axis manipulator. The visual software is structured in three phases: single camera and stereo calibration, addition of the visual inspection tasks for the object to be measured, stereo measurement. The feasibility of the proposed solution has been tested in a real industrial application with strong requirements on robot speed. The comparison of experimental results on a target with a simple and well-defined shape has shown that the proposed solution provides better results, in terms of accuracy and measurement speed, when compared to commercial libraries and RGBD vision systems. Besides, the robot motion policy adopted by the solution proposed here guarantees a continuous movement without the need for stop\&go phases. {\textcopyright} 2015, Springer Science+Business Media Dordrecht.

}, doi = {10.1007/s10846-015-0249-4}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84955089994\&partnerID=40\&md5=9c4abfb9d88e7dff178bbd704c850bbb}, author = {Fulvio, G.D. and Emanuele Frontoni and Adriano Mancini and Primo Zingaretti} } @article {Pierdicca201525, title = {Making visible the invisible. Augmented reality visualization for 3D reconstructions of archaeological sites}, journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {9254}, year = {2015}, note = {cited By 0}, pages = {25-37}, doi = {10.1007/978-3-319-22888-4_3}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84944688602\&partnerID=40\&md5=5988b5e6786fdbcd931f64ac7f8483f5}, author = {Roberto Pierdicca and Emanuele Frontoni and Primo Zingaretti and Eva Savina Malinverni and F. Colosi and R. Orazi} }