Modas, ApostolosSanchez-Matilla, RicardoFrossard, PascalCavallaro, Andrea2020-07-152020-07-152020-07-152020-06-2910.1109/MSP.2020.2985363https://infoscience.epfl.ch/handle/20.500.14299/170125Autonomous vehicles (AVs) rely on accurate and robust sensor observations for safety-critical decision making in a variety of conditions. The fundamental building blocks of such systems are sensors and classifiers that process ultrasound, radar, GPS, lidar, and camera signals [1]. It is of primary importance that the resulting decisions are robust to perturbations, which can take the form of different types of nuisances and data transformations and can even be adversarial perturbations (APs).Adversarial perturbationsAutonomous vehiclesSensorstext::journal::journal article::research article