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Indirectly-Supervised Anomaly Detection of Clinically-Meaningful Health Events from Smart Home Data
Anomaly detection techniques can extract a wealth of information about unusual events. Unfortunately, these methods yield an abundance of findings that are not of interest, obscuring relevant anomalies. In this work, we improve upon traditional anomaly detection methods by introducing Isudra, an Ind...
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| Publicado no: | ACM Trans Intell Syst Technol |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8323613/ https://ncbi.nlm.nih.gov/pubmed/34336375 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1145/3439870 |
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