4 papers
A Feedback-Control Framework for Efficient Dataset Collection from In-Vehicle Data Streams
Philipp Reis, Philipp Rigoll, Christian Steinhauser +2
Modern AI systems are increasingly constrained not by model capacity but by the quality and diversity of their data. Despite growing emphasis on data-centric AI, most datasets are…
Point Cloud Recombination: Systematic Real Data Augmentation Using Robotic Targets for LiDAR Perception Validation
Hubert Padusinski, Christian Steinhauser, Christian Scherl +2
The validation of LiDAR-based perception of intelligent mobile systems operating in open-world applications remains a challenge due to the variability of real environmental conditi…
Data Quality Matters: Quantifying Image Quality Impact on Machine Learning Performance
Christian Steinhauser, Philipp Reis, Hubert Padusinski +2
Precise perception of the environment is essential in highly automated driving systems, which rely on machine learning tasks such as object detection and segmentation. Compression…
The Machine Vision Iceberg Explained: Advancing Dynamic Testing by Considering Holistic Environmental Relations
Hubert Padusinski, Christian Steinhauser, Thilo Braun +2
Machine Vision (MV) is essential for solving driving automation. This paper examines potential shortcomings in current MV testing strategies for highly automated driving (HAD) syst…