Detecting human activities based on a multimodal sensor data set using a bidirectional long short-term memory model: a case study

Research output: Contribution to a Journal (Peer & Non Peer) › Article › peer-review

Original language	English (Ireland)
Number of pages	20
Journal	Challenges and Trends in Multimodal Fall Detection for Healthcare
Publication status	Published - 1 Jan 2020

Authors (Note for portal: view the doc link for the full list of authors)

Authors
de Assis Neto, Silvano Ramos and Santos, Guto Leoni and da Silva Rocha, Elisson and Bendechache, Malika and Rosati, Pierangelo and Lynn, Theo and Takako Endo, Patricia

@article{810844576c314c4f80ab78fe43fd7e2d,

title = "Detecting human activities based on a multimodal sensor data set using a bidirectional long short-term memory model: a case study",

author = "Malika Bendechache",

year = "2020",

month = jan,

day = "1",

language = "English (Ireland)",

journal = "Challenges and Trends in Multimodal Fall Detection for Healthcare",

}