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Enhancing autoencoder models for multivariate time series anomaly detection: the role of noise and data amount: Enhancing autoencoder models for multivariate...: S. T. Sefati et al.

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Title: Enhancing autoencoder models for multivariate time series anomaly detection: the role of noise and data amount: Enhancing autoencoder models for multivariate...: S. T. Sefati et al.
Authors: Sefati, Seyedeh Tina1, t.sefati@tabrizu.ac.ir, Razavi, Seyed Naser1, seyed.razavi@siemens-healthineers.com, Salehpour, Pedram1, psalehpoor@tabrizu.ac.ir
Source: Journal of Supercomputing; Mar2025, Vol. 81 Issue 4, p1-27, 27p
Database: Applied Science & Technology Source
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PubType: Academic Journal
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      – Type: doi
        Value: 10.1007/s11227-025-07044-w
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      – Code: eng
        Text: English
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        PageCount: 27
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      – TitleFull: Enhancing autoencoder models for multivariate time series anomaly detection: the role of noise and data amount: Enhancing autoencoder models for multivariate...: S. T. Sefati et al.
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            NameFull: Sefati, Seyedeh Tina
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            NameFull: Razavi, Seyed Naser
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              Text: Mar2025
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              Value: 81
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