UAV vibrations degrade acoustic tap-testing accuracy for tile defects, but an energy-based filtering approach restores classification performance above 98% when paired with PCA on data from a Stewart platform simulator.
Road disturbance drives a more simplified soundscape in temperate forests revealed by deep learning and acoustics indices
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Integrating acoustic tapping with a UAV platform for tile condition classification
UAV vibrations degrade acoustic tap-testing accuracy for tile defects, but an energy-based filtering approach restores classification performance above 98% when paired with PCA on data from a Stewart platform simulator.