Advances in electrocardiogram signal analytics for person identification using fine-grained fusion-driven deep representation learning under arrhythmic conditions
- DOI
- 10.3389/fdgth.2026.1841911
- Published
- 2026-08-18
- Container
- Frontiers in Digital Health
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/fdgth.2026.1841911,
title = {Advances in electrocardiogram signal analytics for person identification using fine-grained fusion-driven deep representation learning under arrhythmic conditions},
author = {Majed Balkheer and Mahmoud Ragab and Reda Salama and Ashis Kumer Biswas},
year = {2026},
journal = {Frontiers in Digital Health},
doi = {10.3389/fdgth.2026.1841911},
url = {https://doi.org/10.3389/fdgth.2026.1841911}
}RIS
TY - JOUR TI - Advances in electrocardiogram signal analytics for person identification using fine-grained fusion-driven deep representation learning under arrhythmic conditions AU - Majed Balkheer AU - Mahmoud Ragab AU - Reda Salama AU - Ashis Kumer Biswas PY - 2026 JO - Frontiers in Digital Health DO - 10.3389/fdgth.2026.1841911 UR - https://doi.org/10.3389/fdgth.2026.1841911 ER -
APA
Balkheer, M., Ragab, M., Salama, R., & Biswas, A. K. (2026). Advances in electrocardiogram signal analytics for person identification using fine-grained fusion-driven deep representation learning under arrhythmic conditions. Frontiers in Digital Health. https://doi.org/10.3389/fdgth.2026.1841911
Source records
- crossref · retrieved 2026-09-25T07:26:44.577Z