Robust Human Activity Recognition using smartwatches and smartphones
| Autores: | , , , , |
|---|---|
| Formato: | artículo |
| Fecha de publicación: | 2018 |
| País: | España |
| Recursos: | Universidad Politécnica de Madrid |
| Repositorio: | Archivo Digital UPM |
| OAI Identifier: | oai:oa.upm.es:77615 |
| Acesso em linha: | https://oa.upm.es/77615/ |
| Access Level: | acceso abierto |
| Palavra-chave: | Wearable computing Activity recognition Mobile sensing Feature analysis Hidden Markov Models Convolutional Neural Networks Recurrent Neural Networks Long–Short Term Memory |
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oai:oa.upm.es:77615 |
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ES |
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España |
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|
| spelling |
Robust Human Activity Recognition using smartwatches and smartphonesSan Segundo Hernández, Rubén|||0000-0001-9659-5464Blunck, HenrikMoreno Pimentel, José MarianoStisen, AllanGil Martín, Manuel|||0000-0002-4285-6224Wearable computingActivity recognitionMobile sensingFeature analysisHidden Markov ModelsConvolutional Neural NetworksRecurrent Neural NetworksLong–Short Term Memory20182018-01-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articlehttps://oa.upm.es/77615/reponame:Archivo Digital UPMinstname:Universidad Politécnica de MadridEspañolesopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:oa.upm.es:776152026-06-21T12:45:07Z |
| dc.title.none.fl_str_mv |
Robust Human Activity Recognition using smartwatches and smartphones |
| title |
Robust Human Activity Recognition using smartwatches and smartphones |
| spellingShingle |
Robust Human Activity Recognition using smartwatches and smartphones San Segundo Hernández, Rubén|||0000-0001-9659-5464 Wearable computing Activity recognition Mobile sensing Feature analysis Hidden Markov Models Convolutional Neural Networks Recurrent Neural Networks Long–Short Term Memory |
| title_short |
Robust Human Activity Recognition using smartwatches and smartphones |
| title_full |
Robust Human Activity Recognition using smartwatches and smartphones |
| title_fullStr |
Robust Human Activity Recognition using smartwatches and smartphones |
| title_full_unstemmed |
Robust Human Activity Recognition using smartwatches and smartphones |
| title_sort |
Robust Human Activity Recognition using smartwatches and smartphones |
| dc.creator.none.fl_str_mv |
San Segundo Hernández, Rubén|||0000-0001-9659-5464 Blunck, Henrik Moreno Pimentel, José Mariano Stisen, Allan Gil Martín, Manuel|||0000-0002-4285-6224 |
| author |
San Segundo Hernández, Rubén|||0000-0001-9659-5464 |
| author_facet |
San Segundo Hernández, Rubén|||0000-0001-9659-5464 Blunck, Henrik Moreno Pimentel, José Mariano Stisen, Allan Gil Martín, Manuel|||0000-0002-4285-6224 |
| author_role |
author |
| author2 |
Blunck, Henrik Moreno Pimentel, José Mariano Stisen, Allan Gil Martín, Manuel|||0000-0002-4285-6224 |
| author2_role |
author author author author |
| dc.subject.none.fl_str_mv |
Wearable computing Activity recognition Mobile sensing Feature analysis Hidden Markov Models Convolutional Neural Networks Recurrent Neural Networks Long–Short Term Memory |
| topic |
Wearable computing Activity recognition Mobile sensing Feature analysis Hidden Markov Models Convolutional Neural Networks Recurrent Neural Networks Long–Short Term Memory |
| publishDate |
2018 |
| dc.date.none.fl_str_mv |
2018 2018-01-01 |
| dc.type.none.fl_str_mv |
journal article http://purl.org/coar/resource_type/c_6501 |
| dc.type.openaire.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.none.fl_str_mv |
https://oa.upm.es/77615/ |
| url |
https://oa.upm.es/77615/ |
| dc.language.none.fl_str_mv |
Español es |
| language_invalid_str_mv |
Español es |
| dc.rights.none.fl_str_mv |
open access http://purl.org/coar/access_right/c_abf2 |
| dc.rights.openaire.fl_str_mv |
info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
open access http://purl.org/coar/access_right/c_abf2 |
| eu_rights_str_mv |
openAccess |
| dc.source.none.fl_str_mv |
reponame:Archivo Digital UPM instname:Universidad Politécnica de Madrid |
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Universidad Politécnica de Madrid |
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Archivo Digital UPM |
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Archivo Digital UPM |
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1869420442929856512 |
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15,300724 |