Generative Few-Shot Siamese Networks for Anomaly Detection: Application to Pipeline Leakage in Nuclear Power Plants.

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Title: Generative Few-Shot Siamese Networks for Anomaly Detection: Application to Pipeline Leakage in Nuclear Power Plants.
Authors: Jeong JH; Department of Electronic Information System Engineering, Sangmyung University, Cheonan 31066, Republic of Korea., Choi YR; Nuclear System Integrity Sensing and Diagnosis Division, Korea Atomic Energy Research Institute, Daejeon 34057, Republic of Korea., Choi YH; Department of Human Intelligence and Robot Engineering, Sangmyung University, Cheonan 31066, Republic of Korea., Cho DY; Department of Nuclear System Engineering, University of Science and Technology (UST), Daejeon 34113, Republic of Korea., Kim MS; Department of Human Intelligence and Robot Engineering, Sangmyung University, Cheonan 31066, Republic of Korea.
Source: Sensors (Basel, Switzerland) [Sensors (Basel)] 2026 Jul 10; Vol. 26 (14). Date of Electronic Publication: 2026 Jul 10.
Publication Type: Journal Article
Journal Info: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE; PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: Generative Few-Shot Siamese Networks for Anomaly Detection: Application to Pipeline Leakage in Nuclear Power Plants.
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  Data: <searchLink fieldCode="AU" term="%22Jeong+JH%22">Jeong JH</searchLink>; Department of Electronic Information System Engineering, Sangmyung University, Cheonan 31066, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Choi+YR%22">Choi YR</searchLink>; Nuclear System Integrity Sensing and Diagnosis Division, Korea Atomic Energy Research Institute, Daejeon 34057, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Choi+YH%22">Choi YH</searchLink>; Department of Human Intelligence and Robot Engineering, Sangmyung University, Cheonan 31066, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Cho+DY%22">Cho DY</searchLink>; Department of Nuclear System Engineering, University of Science and Technology (UST), Daejeon 34113, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kim+MS%22">Kim MS</searchLink>; Department of Human Intelligence and Robot Engineering, Sangmyung University, Cheonan 31066, Republic of Korea.
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  Data: <searchLink fieldCode="JN" term="%22101204366%22">Sensors (Basel, Switzerland)</searchLink> [Sensors (Basel)] 2026 Jul 10; Vol. 26 (14). <i>Date of Electronic Publication: </i>2026 Jul 10.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22MDPI%22">MDPI </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>101204366 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1424-8220 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2214248220%22">14248220 </searchLink><i>NLM ISO Abbreviation: </i>Sensors (Basel) <i>Subsets: </i>MEDLINE; PubMed not MEDLINE
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        Value: 10.3390/s26144372
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        Text: English
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      – TitleFull: Generative Few-Shot Siamese Networks for Anomaly Detection: Application to Pipeline Leakage in Nuclear Power Plants.
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              Text: 2026 Jul 10
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