Lukas Ewecker

According to our database1, Lukas Ewecker authored at least 16 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
Towards Scenario Retrieval of Real Driving Data with Large Vision-Language Models.
Proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems, 2024

Making Radar Detections Safe for Autonomous Driving: A Review.
Proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems, 2024

An Analysis of Driver-Initiated Takeovers during Assisted Driving and their Effect on Driver Satisfaction.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

Detecting Oncoming Vehicles at Night in Urban Scenarios - An Annotation Proof-Of-Concept.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

Combining Visual Saliency Methods and Sparse Keypoint Annotations to Create Object Representations for Providently Detecting Vehicles at Night.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

A Framework for Localization in a Ground Plan Map based on Radar Perception and Odometry Data.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

Odometry Estimation by Fusing Multiple Radar Sensors and an Inertial Measurement Unit.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023
Provident vehicle detection at night for advanced driver assistance systems.
Auton. Robots, March, 2023

How Important is the Temporal Context to Anticipate Oncoming Vehicles at Night?
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2023

Reducing Computer Vision Dataset Size via Selective Sampling.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

2022
Combining Visual Saliency Methods and Sparse Keypoint Annotations to Providently Detect Vehicles at Night.
CoRR, 2022

A Method for Evaluation and Optimization of Automotive Camera Systems based on Simulated Raw Sensor Data.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2022

Detecting vehicles in the dark in urban environments - A human benchmark.
Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022

2021
A Framework for Simulative Evaluation and Optimization of Point Cloud-Based Automotive Sensor Sets.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021

A Dataset for Provident Vehicle Detection at Night.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

2020
Provident Vehicle Detection at Night: The PVDN Dataset.
CoRR, 2020


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