30 citations · 54 across the 11 of their papers we have counts for
Showing 2022Show all
3 papers · 1 filter
cs.LG2022★ 11 cited
Evaluating Object (mis)Detection from a Safety and Reliability Perspective: Discussion and Measures
Andrea Ceccarelli, Leonardo Montecchi
We argue that object detectors in the safety critical domain should prioritize detection of objects that are most likely to interfere with the actions of the autonomous actor. Espe…
cs.CR2022★ 30 cited
Prepare for Trouble and Make it Double. Supervised and Unsupervised Stacking for AnomalyBased Intrusion Detection
Tommaso Zoppi, Andrea Ceccarelli
In the last decades, researchers, practitioners and companies struggled in devising mechanisms to detect malicious activities originating security threats. Amongst the many solutio…
cs.AI2022
Attacks and Faults Injection in Self-Driving Agents on the Carla Simulator -- Experience Report
Niccolò Piazzesi, Massimo Hong, Andrea Ceccarelli
Machine Learning applications are acknowledged at the foundation of autonomous driving, because they are the enabling technology for most driving tasks. However, the inclusion of t…