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A Hybrid Deep Learning Framework for Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data 

Karadayı, Yıldız; Aydın, Mehmet Nafiz; Öğrenci, Arif Selçuk (Mdpi, 2020)
Multivariate time-series data with a contextual spatial attribute have extensive use for finding anomalous patterns in a wide variety of application domains such as earth science, hurricane tracking, fraud, and disease ...
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A hybrid deep learning framework for unsupervised anomaly detection in multivariate spatio-temporal data 

Karadayı, Yıldız; Aydın, Mehmet Nafiz; Öğrenci, Arif Selçuk (MDPI AG, 2020)
Multivariate time-series data with a contextual spatial attribute have extensive use for finding anomalous patterns in a wide variety of application domains such as earth science, hurricane tracking, fraud, and disease ...
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Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy 

Karadayı, Yıldız; Aydın, Mehmet Nafiz; Ögrenci, Arif Selçuk (Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020)
Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data ...

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Aydın, Mehmet Nafiz (3)
Karadayı, Yıldız (3)
Öğrenci, Arif Selçuk (2)Ögrenci, Arif Selçuk (1)SubjectDeep learning (3)Multivariate data (3)Spatio-temporal anomaly detection (3)CNN (2)Hurricane Katrina (2)Hurricane tracking (2)LSTM (2)Unsupervised learning (2)Anomaly detection (1)Clustering algorithms (1)... View MoreDate Issued2020 (3)Has File(s)true (3)

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