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Using fuzzy logic t...
Using fuzzy logic to enhance classification of human motion primitives
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- Bruno, Barbara (författare)
- Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genova, Genova, Italy
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- Mastrogiovanni, Fulvio (författare)
- Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genova, Genova, Italy
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- Saffiotti, Alessandro, 1960- (författare)
- Örebro universitet,Institutionen för naturvetenskap och teknik,AASS
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- Sgorbissa, Antonio (författare)
- Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genova, Genova, Italy
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(creator_code:org_t)
- Cham : Springer, 2014
- 2014
- Engelska.
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Ingår i: Information processing and management of uncertainty in knowledge-based systems, PT II. - Cham : Springer. - 9783319088549 - 9783319088556 ; , s. 596-605
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- The design of automated systems for the recognition of specific human activities is among the most promising research activities in Ambient Intelligence. The literature suggests the adoption of wearable devices, relying on acceleration information to model the activities of interest and distance metrics for the comparison of such models with the run-time data. Most current solutions do not explicitly model the uncertainty associated with the recognition, but rely on crisp thresholds and comparisons which introduce brittleness and inaccuracy in the system. We propose a framework for the recognition of simple activities in which recognition uncertainty is modelled using possibility distributions. We show that reasoning about this explicitly modelled uncertainty leads to a system with enhanced recognition accuracy and precision.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Activity recognition; Activities of Daily Living; wearable sensors; possibility measures
- Computer Science
- Datavetenskap
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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