Leveraging Interpretability: Concept-based Pedestrian Detection with Deep Neural Networks. - Patrick Feifel; Frank Bonarens; Frank Köster (CSCS, 2021)

Reevaluating the Safety Impact of Inherent Interpretability on Deep Neural Networks for Pedestrian Detection. - Patrick Feifel; Frank Bonarens; Frank Köster (CVPR Workshops, 2021)

Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety. - Sebastian Houben; Stephanie Abrecht; Maram Akila; Andreas Bär; Felix Brockherde; Patrick Feifel; Tim Fingscheidt; Sujan Sai Gannamaneni; Seyed Eghbal Ghobadi; Ahmed Hammam; Anselm Haselhoff; Felix Hauser; et al. (CoRR, 2021)

Using ontologies for dataset engineering in automotive AI applications. - Martin Herrmann; Christian Witt; Laureen Lake; Stefani Guneshka; Christian Heinzemann; Frank Bonarens; Patrick Feifel; Simon Funke (DATE, 2022)

Revisiting the Evaluation of Deep Neural Networks for Pedestrian Detection. - Patrick Feifel; Benedikt Franke; Arne P. Raulf; Friedhelm Schwenker; Frank Bonarens; Frank Köster (AISafety@IJCAI, 2022)

Domain Adaptive Pedestrian Detection Based on Semantic Concepts. - Patrick Feifel; Frank Bonarens; Frank Köster (VISIGRAPP (5: VISAPP), 2023)