Neural Networks for End-to-End Refinement of Simulated Sensor Data for Automotive Applications. - Jörn Thieling; Philip Elspas; Jürgen Roßmann (SysCon, 2019)

Leveraging Regular Expressions for Flexible Scenario Detection in Recorded Driving Data. - Philip Elspas; Jacob Langner; Michael Aydinbas; Johannes Bach; Eric Sax (ISSE, 2020)

Joint Vehicle Trajectory and Cut-In Prediction on Highways using Output Constrained Neural Networks. - Mathis Brosowsky; Paul Orschau; Olaf Dünkel; Philip Elspas; Daniel Slieter; Marius Zöllner 001 (SSCI, 2021)

Time Series Segmentation for Driving Scenario Detection with Fully Convolutional Networks. - Philip Elspas; Yannick Klose; Simon T. Isele; Johannes Bach; Eric Sax (VEHITS, 2021)

Towards a Scenario Database from Recorded Driving Data with Regular Expressions for Scenario Detection. - Philip Elspas; Jonas Lindner; Mathis Brosowsky; Johannes Bach; Eric Sax (VEHITS, 2022)

Towards Scenario Retrieval of Real Driving Data with Large Vision-Language Models. - Tin Stribor Sohn; Maximilian Dillitzer; Lukas Ewecker; Tim Brühl; Robin Schwager; Lena Dalke; Philip Elspas; Frank Oechsle; Eric Sax (VEHITS, 2024)