A Deep Learning Model for Detecting the Arrival Time of Weak Underwater Signals in Fluvial Acoustic Tomography Systems.

Zheng W, Yu X, Peng X, Yang C, Wang S, Chen H, Bu Z, Zhang Y, Zhang Y, Lin L

DOI: 10.3390/s25030922
Published: 2025 Feb 3
Container: Sensors (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/s25030922,
  title = {A Deep Learning Model for Detecting the Arrival Time of Weak Underwater Signals in Fluvial Acoustic Tomography Systems.},
  author = {Zheng W and Yu X and Peng X and Yang C and Wang S and Chen H and Bu Z and Zhang Y and Zhang Y and Lin L},
  year = {2025},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s25030922},
  url = {https://doi.org/10.3390/s25030922}
}

RIS

TY  - JOUR
TI  - A Deep Learning Model for Detecting the Arrival Time of Weak Underwater Signals in Fluvial Acoustic Tomography Systems.
AU  - Zheng W
AU  - Yu X
AU  - Peng X
AU  - Yang C
AU  - Wang S
AU  - Chen H
AU  - Bu Z
AU  - Zhang Y
AU  - Zhang Y
AU  - Lin L
PY  - 2025
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s25030922
UR  - https://doi.org/10.3390/s25030922
ER  -

APA

W, Z., X, Y., X, P., C, Y., S, W., H, C., Z, B., Y, Z., Y, Z., & L, L. (2025). A Deep Learning Model for Detecting the Arrival Time of Weak Underwater Signals in Fluvial Acoustic Tomography Systems.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s25030922

Source records

pubmed · retrieved 2026-09-26T03:15:45.593Z