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Personalized Online Training for Physical Activity monitoring using weak labels
Ulster University.
Ulster University.
Ulster University.
Ulster University.
Vise andre og tillknytning
2018 (engelsk)Inngår i: 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), IEEE, 2018, s. 567-572Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The use of smartphones for activity recognition is becoming common practice. Most approaches use a single pretrained classifier to recognize activities for all users. Research studies, however, have highlighted how a personalized trained classifier could provide better accuracy. Data labeling for ground truth generation, however, is a time-consuming process. The challenge is further exacerbated when opting for a personalized approach that requires user specific datasets to be labeled, making conventional supervised approaches unfeasible. In this work, we present early results on the investigation into a weakly supervised approach for online personalized activity recognition. This paper describes: (i) a heuristic to generate weak labels used for personalized training, (ii) a comparison of accuracy obtained using a weakly supervised classifier against a conventional ground truth trained classifier. Preliminary results show an overall accuracy of 87% of a fully supervised approach against a 74% with the proposed weakly supervised approach.

sted, utgiver, år, opplag, sider
IEEE, 2018. s. 567-572
Emneord [en]
data annotation, weakly supervised learning, smartphone activity recognition
HSV kategori
Forskningsprogram
Distribuerade datorsystem
Identifikatorer
URN: urn:nbn:se:ltu:diva-68146DOI: 10.1109/PERCOMW.2018.8480292Scopus ID: 2-s2.0-85050025511ISBN: 978-1-5386-3227-7 (digital)OAI: oai:DiVA.org:ltu-68146DiVA, id: diva2:1194664
Konferanse
2nd International Workshop on Annotation of useR Data for UbiquitOUs Systems (ARDUOUS 2018), Athens, Greece, March 19-23, 2018
Tilgjengelig fra: 2018-04-03 Laget: 2018-04-03 Sist oppdatert: 2019-01-18bibliografisk kontrollert

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Synnes, KåreHallberg, Josef

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