Pretraining on broad sound events plus on-the-fly augmentations improves out-of-domain true-positive rates for acoustic drone detection at fixed low false-positive rates.
UA V identification from acoustic signals using statistical learning: A state-of-the-art
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.AS 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Improving acoustic drone detection generalization through pretraining and data augmentation
Pretraining on broad sound events plus on-the-fly augmentations improves out-of-domain true-positive rates for acoustic drone detection at fixed low false-positive rates.