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Found 3 papers, 2 papers with code
WAT: Improve the Worst-class Robustness in Adversarial Training
Furthermore, we propose a measurement to evaluate the proposed method in terms of both the average and worst-class accuracies.
Planning Automated Driving with Accident Experience Referencing and Common-sense Inferencing
In this work, we present the concept of an Automated Driving Strategical Brain (ADSB): a framework of a scene perception and scene safety evaluation system that works at a higher abstraction level, incorporating experience referencing, common-sense inferring and goal-and-value judging capabilities, to provide a contextual perspective for decision making within automated driving planning.
SOTIF Entropy: Online SOTIF Risk Quantification and Mitigation for Autonomous Driving
Therefore, this paper proposes the "Self-Surveillance and Self-Adaption System" as a systematic approach to online minimize the SOTIF risk, which aims to provide a systematic solution for monitoring, quantification, and mitigation of inherent and external risks.
