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http://bura.brunel.ac.uk/handle/2438/26046
Title: | A Novel Deep Offline-to-Online Transfer Learning Framework for Pipeline Leakage Detection With Small Samples |
Authors: | Wang, C Wang, Z Liu, W Shen, Y Dong, H |
Keywords: | deep transfer learning (DTL);dynamic threshold;long short-term memory network;pipeline leakage detection (PLD);small samples |
Issue Date: | 23-Nov-2022 |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Citation: | Wang, C. et al. (2022) 'A Novel Deep Offline-to-Online Transfer Learning Framework for Pipeline Leakage Detection With Small Samples', IEEE Transactions on Instrumentation and Measurement, 72, pp. 1 - 13. doi: 10.1109/TIM.2022.3220302. |
URI: | https://bura.brunel.ac.uk/handle/2438/26046 |
DOI: | https://doi.org/10.1109/TIM.2022.3220302 |
ISSN: | 0018-9456 |
Other Identifiers: | ORCID iDs: Zidong Wang https://orcid.org/0000-0002-9576-7401; Weibo Liu https://orcid.org/0000-0002-8169-3261; Yuxuan Shen https://orcid.org/0000-0003-4870-9038; Hongli Dong https://orcid.org/0000-0001-8531-6757. 3503913 |
Appears in Collections: | Dept of Computer Science Research Papers |
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