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Segmentation of Drone Collision Hazards in Airborne RADAR Point Clouds Using PointNet

The dataset is used for semantic segmentation of aerial point clouds to identify multiple collision hazards. It contains 1.2M radar returns acquired during approximately 2 hours of flight time.

Data and Resources

Cite this as

Hector Arroyo, Paul Keir, Dylan Angus, Santiago Matalonga, Svetlozar Georgiev, Mehdi Goli, Gerard Dooly, James Riordan (2024). Dataset: Segmentation of Drone Collision Hazards in Airborne RADAR Point Clouds Using PointNet. https://doi.org/10.57702/igneicgh

DOI retrieved: December 3, 2024

Additional Info

Field Value
Created December 3, 2024
Last update December 3, 2024
Defined In https://doi.org/10.48550/arXiv.2311.03221
Author Hector Arroyo
More Authors
Paul Keir
Dylan Angus
Santiago Matalonga
Svetlozar Georgiev
Mehdi Goli
Gerard Dooly
James Riordan