574 citations · 784 across the 4 of their papers we have counts for
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eess.SP2019★ 574 cited
Machine learning in acoustics: theory and applications
Michael J. Bianco, Peter Gerstoft, James Traer +4
Acoustic data provide scientific and engineering insights in fields ranging from biology and communications to ocean and Earth science. We survey the recent advances and transforma…
physics.ao-ph2019★ 163 cited
Deep-learning source localization using multi-frequency magnitude-only data
Haiqiang Niu, Zaixiao Gong, Emma Ozanich +3
A deep learning approach based on big data is proposed to locate broadband acoustic sources using a single hydrophone in ocean waveguides with uncertain bottom parameters. Several…