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http://hdl.handle.net/10397/106935
| Title: | Denoising and robust temperature extraction for BOTDA systems based on denoising autoencoder and DNN | Authors: | Wang, B Guo, N Wang, L Yu, C Lu, C |
Issue Date: | 2018 | Source: | 26th International Conference on Optical Fiber Sensors, OSA Technical Digest (Optica Publishing Group, 2018), paper WF29 | Abstract: | Denoising autoencoder is used for denoising of the data obtained by the Brillouin optical time-domain analyzer (BOTDA) sensing system and is also used to form the deep neural networks (DNN) for robust temperature information extraction. | Publisher: | Optica Publishing Group | ISBN: | 978-1-943580-50-7 | DOI: | 10.1364/ofs.2018.wf29 | Description: | Optical Fiber Sensors 2018, Lausanne Switzerland, 24-28 September 2018 | Rights: | © 2018 The Author(s) The following publication B. Wang, N. Guo, L. Wang, C. Yu, and C. Lu, "Denoising and Robust Temperature Extraction for BOTDA Systems based on Denoising Autoencoder and DNN," in 26th International Conference on Optical Fiber Sensors, OSA Technical Digest (Optica Publishing Group, 2018), paper WF29 is available at https://doi.org/10.1364/OFS.2018.WF29. |
| Appears in Collections: | Conference Paper |
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| ofs-2018-wf29.pdf | 657.42 kB | Adobe PDF | View/Open |
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