57 citations · 303 across the 63 of their papers we have counts for
6 papers · 1 filter
N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding
Ryan McConville, Raul Santos-Rodriguez, Robert J Piechocki +1
Deep clustering has increasingly been demonstrating superiority over conventional shallow clustering algorithms. Deep clustering algorithms usually combine representation learning…
Location Anomalies Detection for Connected and Autonomous Vehicles
Xiaoyang Wang, Ioannis Mavromatis, Andrea Tassi +2
Future Connected and Automated Vehicles (CAV), and more generally ITS, will form a highly interconnected system. Such a paradigm is referred to as the Internet of Vehicles (herein…
Operating ITS-G5 DSRC over Unlicensed Bands: A City-Scale Performance Evaluation
Ioannis Mavromatis, Andrea Tassi, Robert J. Piechocki
Future Connected and Autonomous Vehicles (CAVs) will be equipped with a large set of sensors. The large amount of generated sensor data is expected to be exchanged with other CAVs…
Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs
Andrea Tassi, Ioannis Mavromatis, Robert Piechocki +4
Future Connected and Automated Vehicles (CAVs) will be supervised by cloud-based systems overseeing the overall security and orchestrating traffic flows. Such systems rely on data…
Efficient Millimeter-Wave Infrastructure Placement for City-Scale ITS
Ioannis Mavromatis, Andrea Tassi, Robert J. Piechocki +1
Millimeter Waves (mmWaves) will play a pivotal role in the next-generation of Intelligent Transportation Systems (ITSs). However, in deep urban environments, sensitivity to blockag…
Secure Data Offloading Strategy for Connected and Autonomous Vehicles
Andrea Tassi, Ioannis Mavromatis, Robert J. Piechocki +1
Connected and Automated Vehicles (CAVs) are expected to constantly interact with a network of processing nodes installed in secure cabinets located at the side of the road -- thus,…