Autonomous UAV navigation system integrates YOLOv11 and DINOv2 to optimize real-time flight for capturing re-ID quality images of patterned wildlife, demonstrated feasible on Kenyan zebras with claimed generalization to other species.
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FAIR^2 Drones is a proposed standard that adds platform metadata and annotation specifications to existing FAIR and AI-ready frameworks so wildlife drone datasets can support ecological analysis, robotics development, and computer vision benchmarking simultaneously.
citing papers explorer
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Autonomous UAV Navigation for Individual Wildlife Re-Identification
Autonomous UAV navigation system integrates YOLOv11 and DINOv2 to optimize real-time flight for capturing re-ID quality images of patterned wildlife, demonstrated feasible on Kenyan zebras with claimed generalization to other species.
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FAIR^2 Drones: An AI-Ready Standard for Cross-Domain Wildlife Drone Datasets
FAIR^2 Drones is a proposed standard that adds platform metadata and annotation specifications to existing FAIR and AI-ready frameworks so wildlife drone datasets can support ecological analysis, robotics development, and computer vision benchmarking simultaneously.