DeepFall: Non-Invasive Fall Detection with Deep Spatio-Temporal Convolutional Autoencoders

Human falls rarely occur; however, detecting falls is very important from the health and safety perspective. Due to the rarity of falls, it is difficult to employ supervised classification techniques to detect them. Moreover, in these highly skewed situations, it is also difficult to extract domain-...

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Vydané v:	Journal of healthcare informatics research Ročník 4; číslo 1; s. 50 - 70
Hlavní autori:	Nogas, Jacob, Khan, Shehroz S., Mihailidis, Alex
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cham Springer International Publishing 01.03.2020
Predmet:	Biomedical Engineering and Bioengineering Computational Biology/Bioinformatics Computational Intelligence Computer Science Data Mining and Knowledge Discovery Health Informatics Research Article Spatio-temporal Convolutional autoencoders Fall detection Anomaly detection
ISSN:	2509-4971, 2509-498X
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