Show simple item record

dc.contributor.authorWijekoon, Anjana
dc.contributor.authorWiratunga, Nirmalie
dc.contributor.authorSani, Sadiq
dc.date.accessioned2019-02-04T16:17:13Z
dc.date.available2019-02-04T16:17:13Z
dc.date.issued2018-07-09en
dc.identifier.citationWIJEKOON, A., WIRATUNGA, N. and SANI, S. 2018. Improving human activity recognition with neural translator models. In Minor, M. (ed.) Workshop proceedings for the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Stockholm: ICCBR [online], pages 96-100. Available from: http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=96en
dc.identifier.urihttp://hdl.handle.net/10059/3280
dc.description.abstractMultiple sensor modalities provide more accurate Human Activity Recognition (HAR) compared to using a single modality, yet the latter is more convenient and less intrusive. It is advantages to create a model which learns from all available sensors; although it is challenging to deploy such model in an environment with fewer sensors, while maintaining reliable performance levels. We address this challenge with Neural Translator, capable of generating missing modalities from available modalities. These can be used to generate missing or 'privileged' modalities at deployment to improve HAR. We evaluate the translator with k-NN classifiers on the SelfBACK HAR dataset and achieve up-to 4.28% performance improvements with generated modalities. This suggests that non-intrusive modalities suited for deployment benefit from translators that generate missing modalities at deployment.en
dc.language.isoengen
dc.publisherICCBR (ORGANISERS)en
dc.rightshttps://creativecommons.org/licenses/by-nc/4.0en
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectHuman activity recognitionen
dc.subjectMachine learningen
dc.subjectPrivileged learningen
dc.titleImproving human activity recognition with neural translator models.en
dc.typeConference publicationsen
dc.publisher.urihttp://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=96en
dcterms.publicationdate2018-07-12en
refterms.accessExceptionNAen
refterms.depositExceptionNAen
refterms.panelBen
refterms.technicalExceptionNAen
refterms.versionAMen
rioxxterms.publicationdate2018-07-09en
rioxxterms.typeConference Paper/Proceeding/Abstracten
rioxxterms.versionAMen


Files in this item

This item appears in the following Collection(s)

Show simple item record

https://creativecommons.org/licenses/by-nc/4.0
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc/4.0