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Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy
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 have a spatial dimension as an additional context which is often expressed in...
| Formato: | Online Artículo Texto |
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| Lenguaje: | English |
| Publicado: |
IEEE
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8668158/ https://www.ncbi.nlm.nih.gov/pubmed/34931155 http://dx.doi.org/10.1109/ACCESS.2020.3022366 |