Zobrazeno 1 - 10
of 121
pro vyhledávání: '"Gotta, Alberto"'
The paper proposes a data-driven approach to air-to-ground channel estimation in a millimeter-wave wireless network on an unmanned aerial vehicle. Unlike traditional centralized learning methods that are specific to certain geographical areas and ina
Externí odkaz:
http://arxiv.org/abs/2305.18856
With the advent of 5G and the anticipated arrival of 6G, there has been a growing research interest in combining mobile networks with Non-Terrestrial Network platforms such as low earth orbit satellites and Geosynchronous Equatorial Orbit satellites
Externí odkaz:
http://arxiv.org/abs/2305.18845
Automatic traffic classification is increasingly important in networking due to the current trend of encrypting transport information (e.g., behind HTTP encrypted tunnels) which prevents intermediate nodes to access end-to-end transport headers. This
Externí odkaz:
http://arxiv.org/abs/2207.04148
Publikováno v:
IEEE Access, Vol. 9, Page(s): 157316 - 157328, 25 November 2021
In the shipping digitalisation process, the peak will be reached with the advent of a wholly autonomous and at the same time safe and reliable ship. Full autonomy could be obtained by two linked Artificial-Intelligence systems representing the ship n
Externí odkaz:
http://arxiv.org/abs/2207.04140
Automatic traffic classification is increasingly becoming important in traffic engineering, as the current trend of encrypting transport information (e.g., behind HTTP-encrypted tunnels) prevents intermediate nodes from accessing end-to-end packet he
Externí odkaz:
http://arxiv.org/abs/2205.00550
Reinforcement Learning (RL) has recently found wide applications in network traffic management and control because some of its variants do not require prior knowledge of network models. In this paper, we present a novel scheduler for real-time multim
Externí odkaz:
http://arxiv.org/abs/2204.13343
Autor:
De Caro, Valerio, Bano, Saira, Machumilane, Achilles, Gotta, Alberto, Cassará, Pietro, Carta, Antonio, Semola, Rudy, Sardianos, Christos, Chronis, Christos, Varlamis, Iraklis, Tserpes, Konstantinos, Lomonaco, Vincenzo, Gallicchio, Claudio, Bacciu, Davide
This paper presents a proof-of-concept implementation of the AI-as-a-Service toolkit developed within the H2020 TEACHING project and designed to implement an autonomous driving personalization system according to the output of an automatic driver's s
Externí odkaz:
http://arxiv.org/abs/2202.01645
Autonomous vehicles (AVs) generate a massive amount of multi-modal data that once collected and processed through Machine Learning algorithms, enable AI-based services at the Edge. In fact, not all these data contain valuable, and informative content
Externí odkaz:
http://arxiv.org/abs/2109.11323
Autor:
Bacciu, Davide, Akarmazyan, Siranush, Armengaud, Eric, Bacco, Manlio, Bravos, George, Calandra, Calogero, Carlini, Emanuele, Carta, Antonio, Cassara, Pietro, Coppola, Massimo, Davalas, Charalampos, Dazzi, Patrizio, Degennaro, Maria Carmela, Di Sarli, Daniele, Dobaj, Jürgen, Gallicchio, Claudio, Girbal, Sylvain, Gotta, Alberto, Groppo, Riccardo, Lomonaco, Vincenzo, Macher, Georg, Mazzei, Daniele, Mencagli, Gabriele, Michail, Dimitrios, Micheli, Alessio, Peroglio, Roberta, Petroni, Salvatore, Potenza, Rosaria, Pourdanesh, Farank, Sardianos, Christos, Tserpes, Konstantinos, Tagliabò, Fulvio, Valtl, Jakob, Varlamis, Iraklis, Veledar, Omar
This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment comprising both virtual and physical resources spanning the edge-cloud
Externí odkaz:
http://arxiv.org/abs/2107.06543
Publikováno v:
In Computer Communications 1 May 2023 205:45-57
