Cargando…
A Correlation-Based Anomaly Detection Model for Wireless Body Area Networks Using Convolutional Long Short-Term Memory Neural Network
As the Internet of Healthcare Things (IoHT) concept emerges today, Wireless Body Area Networks (WBAN) constitute one of the most prominent technologies for improving healthcare services. WBANs are made up of tiny devices that can effectively enhance patient quality of life by collecting and monitori...
Autores principales: | Albattah, Albatul, Rassam, Murad A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8915085/ https://www.ncbi.nlm.nih.gov/pubmed/35271097 http://dx.doi.org/10.3390/s22051951 |
Ejemplares similares
-
Advancements of Data Anomaly Detection Research in Wireless Sensor Networks: A Survey and Open Issues
por: Rassam, Murad A., et al.
Publicado: (2013) -
A Convolutional Neural Network for Improved Anomaly-Based Network Intrusion Detection
por: Al-Turaiki, Isra, et al.
Publicado: (2021) -
Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks
por: Ghimire, Sujan, et al.
Publicado: (2021) -
Abnormal Activity Recognition from Surveillance Videos Using Convolutional Neural Network
por: Habib, Shabana, et al.
Publicado: (2021) -
Exploiting Graphoelements and Convolutional Neural Networks with Long Short Term Memory for Classification of the Human Electroencephalogram
por: Nejedly, P., et al.
Publicado: (2019)