no code implementations • 23 Jan 2024 • Diaeddin Rimawi, Antonio Liotta, Marco Todescato, Barbara Russo
We tested our framework on a real-world case study of a robot collaborating online with the human, when the system is experiencing a disruptive event.
1 code implementation • 8 Nov 2023 • Diaeddin Rimawi, Antonio Liotta, Marco Todescato, Barbara Russo
A Collaborative Artificial Intelligence System (CAIS) works with humans in a shared environment to achieve a common goal.
no code implementations • 13 Jul 2023 • Mario Di Mauro, Giovanni Galatro, Fabio Postiglione, Wei Song, Antonio Liotta
Predicting the behavior of real-time traffic (e. g., VoIP) in mobility scenarios could help the operators to better plan their network infrastructures and to optimize the allocation of resources.
no code implementations • 19 Jun 2021 • Muhammad Usman Yaseen, Ashiq Anjum, Giancarlo Fortino, Antonio Liotta, Amir Hussain
Herein we demonstrate how a feature-fusion strategy of the orientation components leads to further improving visual recognition accuracy to 97\%.
no code implementations • 11 Apr 2021 • Mario Di Mauro, Giovanni Galatro, Giancarlo Fortino, Antonio Liotta
Machine Learning (ML) techniques are becoming an invaluable support for network intrusion detection, especially in revealing anomalous flows, which often hide cyber-threats.
no code implementations • 9 Mar 2021 • Annamaria Ficara, Giacomo Fiumara, Pasquale De Meo, Antonio Liotta
The importance of a node in a social network is identified through a set of measures called centrality.
Social and Information Networks
no code implementations • 3 Mar 2021 • Lucia Cavallaro, Ovidiu Bagdasar, Pasquale De Meo, Giacomo Fiumara, Antonio Liotta
This chapter provides an overview of key methods and tools that may be used for the analysis of criminal networks, which are presented in a real-world case study.
Social and Information Networks Physics and Society
no code implementations • 18 Sep 2020 • Mario Di Mauro, Giovanni Galatro, Antonio Liotta
This leads to interesting guidelines for security managers and computer network practitioners who are looking at the incorporation of neural-based ML into IDS.
3 code implementations • 10 Mar 2020 • Lucia Cavallaro, Annamaria Ficara, Pasquale De Meo, Giacomo Fiumara, Salvatore Catanese, Ovidiu Bagdasar, Antonio Liotta
Herein, we borrow methods and tools from Social Network Analysis to (i) unveil the structure of Sicilian Mafia gangs, based on two real-world datasets, and (ii) gain insights as to how to efficiently disrupt them.
1 code implementation • 7 Jul 2019 • Yan Wang, Wei Song, Giancarlo Fortino, Lizhe Qi, Wenqiang Zhang, Antonio Liotta
Underwater images play a key role in ocean exploration, but often suffer from severe quality degradation due to light absorption and scattering in water medium.
no code implementations • 18 Jul 2017 • Elena Mocanu, Decebal Constantin Mocanu, Phuong H. Nguyen, Antonio Liotta, Michael E. Webber, Madeleine Gibescu, J. G. Slootweg
Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure.
2 code implementations • 15 Jul 2017 • Decebal Constantin Mocanu, Elena Mocanu, Peter Stone, Phuong H. Nguyen, Madeleine Gibescu, Antonio Liotta
Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods.
no code implementations • 18 Oct 2016 • Decebal Constantin Mocanu, Maria Torres Vega, Eric Eaton, Peter Stone, Antonio Liotta
Conceived in the early 1990s, Experience Replay (ER) has been shown to be a successful mechanism to allow online learning algorithms to reuse past experiences.
no code implementations • 25 Apr 2016 • Maria Torres Vega, Decebal Constantin Mocanu, Antonio Liotta
Among the various means to evaluate the quality of video streams, No-Reference (NR) methods have low computation and may be executed on thin clients.
no code implementations • 20 Apr 2016 • Decebal Constantin Mocanu, Haitham Bou Ammar, Luis Puig, Eric Eaton, Antonio Liotta
Estimation, recognition, and near-future prediction of 3D trajectories based on their two dimensional projections available from one camera source is an exceptionally difficult problem due to uncertainty in the trajectories and environment, high dimensionality of the specific trajectory states, lack of enough labeled data and so on.
no code implementations • 20 Apr 2016 • Decebal Constantin Mocanu, Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu, Antonio Liotta
Thirdly, we show that, for a fixed number of weights, our proposed sparse models (which by design have a higher number of hidden neurons) achieve better generative capabilities than standard fully connected RBMs and GRBMs (which by design have a smaller number of hidden neurons), at no additional computational costs.
no code implementations • 28 Mar 2013 • Aravind Kota Gopalakrishna, Tanir Ozcelebi, Antonio Liotta, Johan J. Lukkien
In machine learning, the choice of a learning algorithm that is suitable for the application domain is critical.