Enhancing COVID-19 tracking apps with human activity recognition using a deep convolutional neural n...
Enhancing COVID-19 tracking apps with human activity recognition using a deep convolutional neural network and HAR-images
About this item
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Author / Creator
Publisher
London: Springer London
Journal title
Language
English
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Publication information
Publisher
London: Springer London
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Scope and Contents
Contents
With the emergence of COVID-19, mobile health applications have increasingly become crucial in contact tracing, information dissemination, and pandemic control in general. Apps warn users if they have been close to an infected person for sufficient time, and therefore potentially at risk. The distance measurement accuracy heavily affects the probab...
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Full title
Enhancing COVID-19 tracking apps with human activity recognition using a deep convolutional neural network and HAR-images
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8009079
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8009079
Other Identifiers
ISSN
0941-0643
E-ISSN
1433-3058
DOI
10.1007/s00521-021-05913-y
