BeamLearning: An end-to-end deep learning approach for the angular localization of sound sources using raw multichannel acoustic pressure data.
- DOI
- 10.1121/10.0005046
- Published
- 2021 Jun
- Container
- The Journal of the Acoustical Society of America
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1121/10.0005046,
title = {BeamLearning: An end-to-end deep learning approach for the angular localization of sound sources using raw multichannel acoustic pressure data.},
author = {Pujol H and Bavu É and Garcia A},
year = {2021},
journal = {The Journal of the Acoustical Society of America},
doi = {10.1121/10.0005046},
url = {https://doi.org/10.1121/10.0005046}
}RIS
TY - JOUR TI - BeamLearning: An end-to-end deep learning approach for the angular localization of sound sources using raw multichannel acoustic pressure data. AU - Pujol H AU - Bavu É AU - Garcia A PY - 2021 JO - The Journal of the Acoustical Society of America DO - 10.1121/10.0005046 UR - https://doi.org/10.1121/10.0005046 ER -
APA
H, P., É, B., & A, G. (2021). BeamLearning: An end-to-end deep learning approach for the angular localization of sound sources using raw multichannel acoustic pressure data.. The Journal of the Acoustical Society of America. https://doi.org/10.1121/10.0005046
Source records
- pubmed · retrieved 2026-09-27T14:27:31.221Z