Electrocardiogram Biometrics Using Transformer’s Self-Attention Mechanism for Sequence Pair Feature Extractor and Flexible Enrollment Scope Identification

The existing electrocardiogram (ECG) biometrics do not perform well when ECG changes after the enrollment phase because the feature extraction is not able to relate ECG collected during enrollment and ECG collected during classification. In this research, we propose the sequence pair feature extract...

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Detalles Bibliográficos
Autores principales: Chee, Kai Jye, Ramli, Dzati Athiar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100332/
https://www.ncbi.nlm.nih.gov/pubmed/35591136
http://dx.doi.org/10.3390/s22093446

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100332/
https://www.ncbi.nlm.nih.gov/pubmed/35591136
http://dx.doi.org/10.3390/s22093446

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