Uncrewed Aircraft Detection from YAMNET Embedding Dataset

This dataset is the main dataset used by the UA Detection Team here at Embry-Riddle Aeronautical University. It provides the ability to conduct binary drone/no drone classification as well as specific drone sub-type classifcation. Dataset is gathered from field data from drones flown by the Unavail research team. Each clip of audio is fed through YAMNET to generate points in an embedding space. The no_drone directory contains various sounds from ambient noise to cars and jets. drone contains samples from the DJI Matrice M100, the Mavic 3, and the Mavic Mini 2. There are 9108 samples total across all the directories. Each .tfdata segment represents a single second of audio.