7 citations · 7 across the 4 of their papers we have counts for
10 papers · 1 filter
Datasets for Lane Detection in Autonomous Driving: A Comprehensive Review
Jörg Gamerdinger, Sven Teufel, Oliver Bringmann
Accurate lane detection is essential for automated driving, enabling safe and reliable vehicle navigation across a variety of road scenarios. Numerous datasets have been introduced…
Image Compression with Bubble-Aware Frame Rate Adaptation for Energy-Efficient Video Capsule Endoscopy
Oliver Bause, Jörg Gamerdinger, Julia Werner +1
Video Capsule Endoscopy (VCE) is a promising method for improving the medical examination of the small intestine in the gastrointestinal tract. A key challenge is their limited siz…
Criticality Metrics for Relevance Classification in Safety Evaluation of Object Detection in Automated Driving
Jörg Gamerdinger, Sven Teufel, Stephan Amann +1
Ensuring safety is the primary objective of automated driving, which necessitates a comprehensive and accurate perception of the environment. While numerous performance evaluation…
LSM: A Comprehensive Metric for Assessing the Safety of Lane Detection Systems in Autonomous Driving
Jörg Gamerdinger, Sven Teufel, Stephan Amann +2
Comprehensive perception of the vehicle's environment and correct interpretation of the environment are crucial for the safe operation of autonomous vehicles. The perception of sur…
SnowyLane: Robust Lane Detection on Snow-covered Rural Roads Using Infrastructural Elements
Jörg Gamerdinger, Benedict Wetzel, Patrick Schulz +2
Lane detection for autonomous driving in snow-covered environments remains a major challenge due to the frequent absence or occlusion of lane markings. In this paper, we present a…
S2S-Net: Addressing the Domain Gap of Heterogeneous Sensor Systems in LiDAR-Based Collective Perception
Sven Teufel, Jörg Gamerdinger, Oliver Bringmann
Collective Perception (CP) has emerged as a promising approach to overcome the limitations of individual perception in the context of autonomous driving. Various approaches have be…