Learning Compact Features for Human Activity Recognition Via Probabilistic First-Take-All
With the popularity of mobile sensor technology, smart wearable devices open a unprecedented opportunity to solve the challenging human activity recognition (HAR) problem by learning expressive representations from the multi-dimensional daily sensor signals. This inspires us to develop a new algorit...
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Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 42(2020), 1 vom: 08. Jan., Seite 126-139
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| 1. Verfasser: |
Ye, Jun
(VerfasserIn) |
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| Weitere Verfasser: |
Qi, Guo-Jun,
Zhuang, Naifan,
Hu, Hao,
Hua, Kien A |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2020
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article
Research Support, U.S. Gov't, Non-P.H.S. |
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