Cargando…
A Study on User Recognition Using the Generated Synthetic Electrocardiogram Signal
Electrocardiogram (ECG) signals are time series data that are acquired by time change. A problem with these signals is that comparison data that have the same size as the registration data must be acquired every time. A network model of an auxiliary classifier based generative adversarial neural net...
Autores principales: | Kim, Min-Gu, Pan, Sung Bum |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7962649/ https://www.ncbi.nlm.nih.gov/pubmed/33800324 http://dx.doi.org/10.3390/s21051887 |
Ejemplares similares
-
Intelligent Deep Models Based on Scalograms of Electrocardiogram Signals for Biometrics
por: Byeon, Yeong-Hyeon, et al.
Publicado: (2019) -
The usefulness of electrocardiogram in the recognition of cardiac transplant rejection
por: Cheema, Huzaifa A., et al.
Publicado: (2022) -
Design and technical validation to generate a synthetic 12-lead electrocardiogram dataset to promote artificial intelligence research
por: Yoo, Hakje, et al.
Publicado: (2023) -
Driver Identification System Using Normalized Electrocardiogram Based on Adaptive Threshold Filter for Intelligent Vehicles
por: Choi, Gyu Ho, et al.
Publicado: (2020) -
Electrocardiogram (ECG)-Based User Authentication Using Deep Learning Algorithms
por: Agrawal, Vibhav, et al.
Publicado: (2023)