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Smart Annotation of Cyclic Data Using Hierarchical Hidden Markov Models
Cyclic signals are an intrinsic part of daily life, such as human motion and heart activity. The detailed analysis of them is important for clinical applications such as pathological gait analysis and for sports applications such as performance analysis. Labeled training data for algorithms that ana...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5676753/ https://www.ncbi.nlm.nih.gov/pubmed/29027973 http://dx.doi.org/10.3390/s17102328 |