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Found 6 papers, 0 papers with code
Hierarchical Insights: Exploiting Structural Similarities for Reliable 3D Semantic Segmentation
Safety-critical applications like autonomous driving call for robust 3D environment perception algorithms which can withstand highly diverse and ambiguous surroundings.
On the Calibration of Uncertainty Estimation in LiDAR-based Semantic Segmentation
We propose a metric to measure the confidence calibration quality of a semantic segmentation model with respect to individual classes.
Survey on LiDAR Perception in Adverse Weather Conditions
The active LiDAR sensor is able to create an accurate 3D representation of a scene, making it a valuable addition for environment perception for autonomous vehicles.
On the calibration of underrepresented classes in LiDAR-based semantic segmentation
The calibration of deep learning-based perception models plays a crucial role in their reliability.
A Survey on Deep Domain Adaptation for LiDAR Perception
Scalable systems for automated driving have to reliably cope with an open-world setting.
Driver Drowsiness Classification Based on Eye Blink and Head Movement Features Using the k-NN Algorithm
A concluding analysis of the best performing feature sets yields valuable insights about the influence of drowsiness on the driver's blink behavior and head movements.
