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sEMG-Based Hand-Gesture Classification Using a Generative Flow Model
Conventional pattern-recognition algorithms for surface electromyography (sEMG)-based hand-gesture classification have difficulties in capturing the complexity and variability of sEMG. The deep structures of deep learning enable the method to learn high-level features of data to improve both accurac...
Autores principales: | Sun, Wentao, Liu, Huaxin, Tang, Rongyu, Lang, Yiran, He, Jiping, Huang, Qiang |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6515175/ https://www.ncbi.nlm.nih.gov/pubmed/31027292 http://dx.doi.org/10.3390/s19081952 |
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