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20242026
most citedSynDroneVision: A Synthetic Dataset for Image-Based Drone Detection

13 citations · 25 across the 6 of their papers we have counts for

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cs.CV2026

Adapting a Foundation Model for Lunar Surface Height Estimation

Patrick Bauer, Marius Schwinning, Melanie Siegel +2

Digital elevation models (DEMs) can provide accurate height information, making it invaluable for analyzing the lunar surface. As the European Space Agency (ESA) prepares for futur…

cs.CV2026

Beyond Clear Skies: Synthetic Seasonal and Weather Variations for Real-World Drone Detection

Tamara R. Lenhard, Andreas Weinmann, Tobias Koch

Reliable drone detection under real-world deployment conditions requires training data that spans the full operational design domain, including adverse weather and seasonal appeara…

cs.CV2026

Vision-Language Model for Accurate Crater Detection

Patrick Bauer, Marius Schwinning, Florian Renk +2

The European Space Agency (ESA), driven by its ambitions on planned lunar missions with the Argonaut lander, has a profound interest in reliable crater detection, since craters pos…

cs.CV2026

Detector-Augmented SAMURAI for Long-Duration Drone Tracking

Tamara R. Lenhard, Andreas Weinmann, Hichem Snoussi +1

Robust long-term tracking of drone is a critical requirement for modern surveillance systems, given their increasing threat potential. While detector-based approaches typically ach…

cs.CV2025

Performance Optimization of YOLO-FEDER FusionNet for Robust Drone Detection in Visually Complex Environments

Tamara R. Lenhard, Andreas Weinmann, Tobias Koch

Drone detection in visually complex environments remains challenging due to background clutter, small object scale, and camouflage effects. While generic object detectors like YOLO…

cs.CV2024★ 13 cited

SynDroneVision: A Synthetic Dataset for Image-Based Drone Detection

Tamara R. Lenhard, Andreas Weinmann, Kai Franke +1

Developing robust drone detection systems is often constrained by the limited availability of large-scale annotated training data and the high costs associated with real-world data…

cs.CV2024★ 12 cited

YOLO-FEDER FusionNet: A Novel Deep Learning Architecture for Drone Detection

Tamara R. Lenhard, Andreas Weinmann, Stefan Jäger +1

Predominant methods for image-based drone detection frequently rely on employing generic object detection algorithms like YOLOv5. While proficient in identifying drones against hom…