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DOE OSTI · 3024379

Explosion Detection using Transfer Learning via YAMNet [Poster]

Takazawa, Samuel Kei·Garces, Milton·Ocampo Giraldo, Luis A.·Hix, Jay D.·Chichester, David L.·Zeiler, Cleat
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Abstract

The acoustic data of explosions and noise collected on smartphones were fed to the YAMNet model to obtain the scores of each class. The data was split 60/20/20 for training, validation, and testing. A single-layered neural network was trained using the computed scores to predict if the data was an explosion or noise. The trained model was then combined with the YAMNet model. The combined model was tested with the ESC-50 dataset to investigate overall accuracy and class based false positive rates.

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Takazawa, Samuel Kei, Garces, Milton, Ocampo Giraldo, Luis A., Hix, Jay D., Chichester, David L., Zeiler, Cleat. 2022-05-20. Explosion Detection using Transfer Learning via YAMNet [Poster]. https://doi.org/10.2172/3024379

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