2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.RO2025
From Real-World Traffic Data to Relevant Critical Scenarios
Florian Lüttner, Nicole Neis, Daniel Stadler +5
The reliable operation of autonomous vehicles, automated driving functions, and advanced driver assistance systems across a wide range of relevant scenarios is critical for their d…
cs.CV2025★ 1 cited
Measuring the Effect of Background on Classification and Feature Importance in Deep Learning for AV Perception
Anne Sielemann, Valentin Barner, Stefan Wolf +3
Common approaches to explainable AI (XAI) for deep learning focus on analyzing the importance of input features on the classification task in a given model: saliency methods like S…
cs.RO2025★ 2 cited
Physically-Based Simulation of Automotive LiDAR
L. Dudzik, M. Roschani, A. Sielemann +4
We present an analytic model for simulating automotive time-of-flight (ToF) LiDAR that includes blooming, echo pulse width, and ambient light, along with steps to determine model p…