Lightweight Graph Neural Network-Driven Acoustic Anomaly Detection Method for Gas Pipeline Leakage Levels in Underground Utility Tunnels.
- DOI
- 10.3390/s26134114
- Published
- 2026 Jun 29
- Container
- Sensors (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/s26134114,
title = {Lightweight Graph Neural Network-Driven Acoustic Anomaly Detection Method for Gas Pipeline Leakage Levels in Underground Utility Tunnels.},
author = {Sun W and Li Y and Yang J and Cheng Y},
year = {2026},
journal = {Sensors (Basel, Switzerland)},
doi = {10.3390/s26134114},
url = {https://doi.org/10.3390/s26134114}
}RIS
TY - JOUR TI - Lightweight Graph Neural Network-Driven Acoustic Anomaly Detection Method for Gas Pipeline Leakage Levels in Underground Utility Tunnels. AU - Sun W AU - Li Y AU - Yang J AU - Cheng Y PY - 2026 JO - Sensors (Basel, Switzerland) DO - 10.3390/s26134114 UR - https://doi.org/10.3390/s26134114 ER -
APA
W, S., Y, L., J, Y., & Y, C. (2026). Lightweight Graph Neural Network-Driven Acoustic Anomaly Detection Method for Gas Pipeline Leakage Levels in Underground Utility Tunnels.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26134114
Source records
- pubmed · retrieved 2026-09-25T12:16:11.878Z