Jacob Langner

According to our database, Jacob Langner authored at least 22 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Generative AI in Systems Engineering: A Framework for Risk Assessment of Large Language Models.

Stefan Otten, Philipp Reis, Philipp Rigoll, Joshua Ransiek, Tobias Schürmann, Jacob Langner, Eric Sax

CoRR, February, 2026

2025

A Feedback-Control Framework for Efficient Dataset Collection from In-Vehicle Data Streams.

Philipp Reis, Philipp Rigoll, Christian Steinhauser, Jacob Langner, Eric Sax

CoRR, November, 2025

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording.

Philipp Reis, Joshua Ransiek, David Petri, Jacob Langner, Eric Sax

CoRR, July, 2025

Point Cloud Recombination: Systematic Real Data Augmentation Using Robotic Targets for LiDAR Perception Validation.

Hubert Padusinski, Christian Steinhauser, Christian Scherl, Julian Gaal, Jacob Langner

CoRR, May, 2025

Data Quality Matters: Quantifying Image Quality Impact on Machine Learning Performance.

Christian Steinhauser, Philipp Reis, Hubert Padusinski, Jacob Langner, Eric Sax

Proceedings of the IEEE Intelligent Vehicles Symposium, 2025

A Data-Driven Novelty Score for Diverse in-Vehicle Data Recording.

Philipp Reis, Joshua Ransiek, David Petri, Tobias Schürmann, Jacob Langner, Eric Sax

Proceedings of the 28th IEEE International Conference on Intelligent Transportation Systems, 2025

2024

Unveiling Objects with SOLA: An Annotation-Free Image Search on the Object Level for Automotive Data Sets.

Philipp Rigoll, Jacob Langner, Lennart Ries, Eric Sax

Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

Detecting Oncoming Vehicles at Night in Urban Scenarios - An Annotation Proof-Of-Concept.

Lukas Ewecker, Niklas Wagner, Tim Brühl, Robin Schwager, Tin Stribor Sohn, Alexander Engelsberger, Jensun Ravichandran, Hanno Stage, Jacob Langner, Sascha Saralajew

Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

GOOSE: Goal-Conditioned Reinforcement Learning for Safety-Critical Scenario Generation.

Joshua Ransiek, Johannes Plaum, Jacob Langner, Eric Sax

Proceedings of the 27th IEEE International Conference on Intelligent Transportation Systems, 2024

Contextualizing the Sim-to-Real Gap for Hardware-in-the-Loop Testing of Highly Automated Driving Functions.

Christian Steinhauser, Joshua Ransiek, Jacob Langner, Eric Sax

Proceedings of the 8th International Conference on System Reliability and Safety, 2024

2023

Unveiling Objects with SOLA: An Annotation-Free Image Search on the Object Level for Automotive Data Sets.

Philipp Rigoll, Jacob Langner, Eric Sax

CoRR, 2023

Reducing Computer Vision Dataset Size via Selective Sampling.

Hanno Stage, Lukas Ewecker, Jacob Langner, Tin Stribor Sohn, Thomas Villmann, Eric Sax

Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems, 2023

2022

An Efficient Strategy for Testing ADAS on HiL Test Systems with Parallel Condition-based Assessments.

Christian Steinhauser, Maciej Boncler, Jacob Langner, Steffen Strebel, Eric Sax

Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems, 2022

2021

Capturing the Variety of Urban Logical Scenarios from Bird-view Trajectories.

Christian King, Thilo Braun, Constantin Braess, Jacob Langner, Eric Sax

Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems, 2021

2020

Qualitative Feature Assessment for Longitudinal and Lateral Control-features.

Jacob Langner, Christian Seiffer, Stefan Otten, Kai-Lukas Bauer, Marc Holzäpfel, Eric Sax

Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems, 2020

A Process Reference Model for the Virtual Application of Predictive Control Features.

Jacob Langner, Kai-Lukas Bauer, Marc Holzäpfel, Eric Sax

Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

A Taxonomy and Survey on Validation Approaches for Automated Driving Systems.

Christian King, Lennart Ries, Jacob Langner, Eric Sax

Proceedings of the IEEE International Symposium on Systems Engineering, 2020

Leveraging Regular Expressions for Flexible Scenario Detection in Recorded Driving Data.

Philip Elspas, Jacob Langner, Michael Aydinbas, Johannes Bach, Eric Sax

Proceedings of the IEEE International Symposium on Systems Engineering, 2020

2019

Logical Scenario Derivation by Clustering Dynamic-Length-Segments Extracted from Real-World-Driving-Data.

Jacob Langner, Hannes Grolig, Stefan Otten, Marc Holzäpfel, Eric Sax

Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems, 2019

A Driving Scenario Representation for Scalable Real-Data Analytics with Neural Networks.

Lennart Ries, Jacob Langner, Stefan Otten, Johannes Bach, Eric Sax

Proceedings of the 2019 IEEE Intelligent Vehicles Symposium, 2019

2018

Estimating the Uniqueness of Test Scenarios derived from Recorded Real-World-Driving-Data using Autoencoders.

Jacob Langner, Johannes Bach, Lennart Ries, Stefan Otten, Marc Holzäpfel, Eric Sax

Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018

2017

Test scenario selection for system-level verification and validation of geolocation-dependent automotive control systems.

Johannes Bach, Jacob Langner, Stefan Otten, Eric Sax, Marc Holzäpfel

Proceedings of the International Conference on Engineering, Technology and Innovation, 2017