Individual Identification by Late Information Fusion of EmgCNN and EmgLSTM from Electromyogram Signals

This paper is concerned with individual identification by late fusion of two-stream deep networks from Electromyogram (EMG) signals. EMG signal has more advantages on security compared to other biosignals exposed visually, such as the face, iris, and fingerprints, when used for biometrics, at least...

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Detalles Bibliográficos
Autores principales: Byeon, Yeong-Hyeon, Kwak, Keun-Chang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9504259/
https://www.ncbi.nlm.nih.gov/pubmed/36146119
http://dx.doi.org/10.3390/s22186770

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9504259/
https://www.ncbi.nlm.nih.gov/pubmed/36146119
http://dx.doi.org/10.3390/s22186770

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