Paper

In this paper, we propose a method for post-hoc explainability of black-box models. The key component of the semantic and quantitative local explanation is a knowledge distillation (KD) process which is used to mimic the […]

Modern neural networks have found to be miscalibrated in terms of confidence calibration, i.e., their predicted confidence scores do not reflect the observed accuracy or precision. Recent work has introduced methods for post-hoc confidence calibration […]

Bei der Entwicklung hin zu einer automatisierten und vernetzten Mobilität wird in der (breiteren) Öffentlichkeit oft der Eindruck vermittelt, als sei die Technik bereits so weit fortgeschritten, dass eine problemlose Umsetzung kurzfristig möglich sei. Aktuell […]

Currently, car assistant systems mainly try to prevent accidents. Increasing built-in car technology also extends the potential applications in vehicles. Future cars might have virtual windshields that augment the traffic or individual virtual assistants interacting […]

Understanding user needs and behavior in automated vehicles (AVs) while traveling is essential for future in-vehicle interface and service design. Since AVs are not yet market-ready, current knowledge about AV use and perception is based […]

Unbiased confidence estimates of neural networks are crucial especially for safety-critical applications. Many methods have been developed to calibrate biased confidence estimates. Though there is a variety of methods for classification, the field of object […]

Ansätze und Methoden zur erfolgreichen Umsetzung neuer Mobilitätskonzepte Autonome Fahrzeuge und Flugtaxis, die per Smartphone bedarfsgerecht angefordert und über eine App abgerechnet werden, Transportdrohnen, die Güter zustellen, etc. – mit solchen Bildern vermitteln die beteiligten […]