Long-Distance Pipeline Intrusion Warning Based on Environment Embedding from Distributed Optical Fiber Sensing
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-44204-9_22
Reference24 articles.
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2. Shen, J., Yang, K., Zhu, C., et al.: Third-party construction intrusion detection of natural gas pipelines based on improved YOLOv. In: 2022 Chinese Automation Congress (CAC), pp. 1844–1849, Xiamen (2022). https://doi.org/10.1109/CAC57257.2022.10054804
3. Yang, Y., Li, Y., Zhang, H.: Pipeline safety early warning method for distributed signal using bilinear CNN and LightGBM. In: Proceeding of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2021), Toronto (2021)
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