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A Competitive Approach for Human Activity Recognition on Smartphones
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-1971-4295
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany.
2013 (English)In: ESANN 2013, ESANN , 2013, 455-460 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes a competitive approach developed for an activity recognition challenge. The competition was defined on a new and publicly available dataset of human activities, recorded with smartphone sensors. This work investigates different feature sets for the activity recognition task of the competition. Moreover, the focus is also on the introduction of a new, confidence-based boosting algorithm called ConfAda- Boost.M1. Results show that the new classification method outperforms commonly used classifiers, such as decision trees or AdaBoost.M1.

Place, publisher, year, edition, pages
ESANN , 2013. 455-460 p.
National Category
Signal Processing Information Systems
Identifiers
URN: urn:nbn:se:liu:diva-97302ISBN: 978-2-87419-081-0 (print)OAI: oai:DiVA.org:liu-97302DiVA: diva2:646274
Conference
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2013), 24-26 April, Bruges, Belgium
Available from: 2013-09-07 Created: 2013-09-07 Last updated: 2015-09-22Bibliographically approved

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Hendeby, Gustaf

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf