Search Results for author: Leonardo M. Millefiori

Found 9 papers, 1 papers with code

Monitoring of Underwater Critical Infrastructures: the Nord Stream and Other Recent Case Studies

no code implementations3 Feb 2023 Giovanni Soldi, Domenico Gaglione, Simone Raponi, Nicola Forti, Enrica d'Afflisio, Paweł Kowalski, Leonardo M. Millefiori, Dimitris Zissis, Paolo Braca, Peter Willett, Alain Maguer, Sandro Carniel, Giovanni Sembenini, Catherine Warner

The explosions on September 26th, 2022, which damaged the gas pipelines of Nord Stream 1 and Nord Stream 2, have highlighted the need and urgency of improving the resilience of Underwater Critical Infrastructures (UCIs).

Statistical Hypothesis Testing Based on Machine Learning: Large Deviations Analysis

no code implementations22 Jul 2022 Paolo Braca, Leonardo M. Millefiori, Augusto Aubry, Stefano Marano, Antonio De Maio, Peter Willett

In other words, the classification error probability convergence to zero and its rate can be computed on a portion of the dataset available for training.

BIG-bench Machine Learning

Recurrent Encoder-Decoder Networks for Vessel Trajectory Prediction with Uncertainty Estimation

no code implementations11 May 2022 Samuele Capobianco, Nicola Forti, Leonardo M. Millefiori, Paolo Braca, Peter Willett

Recent deep learning methods for vessel trajectory prediction are able to learn complex maritime patterns from historical Automatic Identification System (AIS) data and accurately predict sequences of future vessel positions with a prediction horizon of several hours.

Trajectory Prediction Uncertainty Quantification

Quickest Detection and Forecast of Pandemic Outbreaks: Analysis of COVID-19 Waves

no code implementations12 Jan 2021 Giovanni Soldi, Nicola Forti, Domenico Gaglione, Paolo Braca, Leonardo M. Millefiori, Stefano Marano, Peter Willett, Krishna Pattipati

The COVID-19 pandemic has, worldwide and up to December 2020, caused over 1. 7 million deaths, and put the world's most advanced healthcare systems under heavy stress.

Deep Learning Methods for Vessel Trajectory Prediction based on Recurrent Neural Networks

1 code implementation7 Jan 2021 Samuele Capobianco, Leonardo M. Millefiori, Nicola Forti, Paolo Braca, Peter Willett

Experimental results on vessel trajectories from an AIS dataset made freely available by the Danish Maritime Authority show the effectiveness of deep-learning methods for trajectory prediction based on sequence-to-sequence neural networks, which achieve better performance than baseline approaches based on linear regression or on the Multi-Layer Perceptron (MLP) architecture.

Trajectory Prediction

Space-based Global Maritime Surveillance. Part II: Artificial Intelligence and Data Fusion Techniques

no code implementations23 Nov 2020 Giovanni Soldi, Domenico Gaglione, Nicola Forti, Alessio Di Simone, Filippo Cristian Daffinà, Gianfausto Bottini, Dino Quattrociocchi, Leonardo M. Millefiori, Paolo Braca, Sandro Carniel, Peter Willett, Antonio Iodice, Daniele Riccio, Alfonso Farina

Maritime surveillance (MS) is of paramount importance for search and rescue operations, fishery monitoring, pollution control, law enforcement, migration monitoring, and national security policies.

Space-based Global Maritime Surveillance. Part I: Satellite Technologies

no code implementations23 Nov 2020 Giovanni Soldi, Domenico Gaglione, Nicola Forti, Alessio Di Simone, Filippo Cristian Daffinà, Gianfausto Bottini, Dino Quattrociocchi, Leonardo M. Millefiori, Paolo Braca, Sandro Carniel, Peter Willett, Antonio Iodice, Daniele Riccio, Alfonso Farina

Maritime surveillance (MS) is crucial for search and rescue operations, fishery monitoring, pollution control, law enforcement, migration monitoring, and national security policies.

Quickest Detection of COVID-19 Pandemic Onset

no code implementations20 Nov 2020 Paolo Braca, Domenico Gaglione, Stefano Marano, Leonardo M. Millefiori, Peter Willett, Krishna Pattipati

This paper develops an easily-implementable version of Page's CUSUM quickest-detection test, designed to work in certain composite hypothesis scenarios with time-varying data statistics.

Time Series Analysis

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