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A data-efficient active learning architecture for anomaly detection in industrial time series data.

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Title: A data-efficient active learning architecture for anomaly detection in industrial time series data.
Authors: Holtz, David1 (AUTHOR), Kaymakci, Can2,3 (AUTHOR), Leuthe, Daniel4,5 (AUTHOR) daniel.leuthe@fim-rc.de, Wenninger, Simon4,5 (AUTHOR), Sauer, Alexander2,3 (AUTHOR)
Source: Flexible Services & Manufacturing Journal. Jun2026, Vol. 38 Issue 2, p618-649. 32p.
Database: Business Source Ultimate
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An: 195094007
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PubType: Academic Journal
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  Data: <searchLink fieldCode="JN" term="%22Flexible+Services+%26+Manufacturing+Journal%22">Flexible Services & Manufacturing Journal</searchLink>. Jun2026, Vol. 38 Issue 2, p618-649. 32p.
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        Value: 10.1007/s10696-024-09588-0
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      – Code: eng
        Text: English
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            NameFull: Holtz, David
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            NameFull: Kaymakci, Can
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            NameFull: Leuthe, Daniel
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              Text: Jun2026
              Type: published
              Y: 2026
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