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RFUAV contains 1.3 TB of raw radio-frequency (RF) signal data collected from 37 distinct unmanned aerial vehicle (UAV) models for detection and identification tasks. Developed by kitofrank and released in 2025, this benchmark provides high-volume signal data to address the limitations of smaller, less diverse drone signal repositories.
The dataset is provided in an imagefolder format and requires approximately 1.3 TB of disk space; users should ensure high-speed storage is available for training.