A Low-Power Wireless System for Predicting Early Signs of Sudden Cardiac Arrest Incorporating an Optimized CNN Model Implemented on NVIDIA Jetson.
- DOI
- 10.3390/s23042270
- Published
- 2023 Feb 17
- Container
- Sensors (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/s23042270,
title = {A Low-Power Wireless System for Predicting Early Signs of Sudden Cardiac Arrest Incorporating an Optimized CNN Model Implemented on NVIDIA Jetson.},
author = {Kota VD and Sharma H and Albert MV and Mahbub I and Mehta G and Namuduri K},
year = {2023},
journal = {Sensors (Basel, Switzerland)},
doi = {10.3390/s23042270},
url = {https://doi.org/10.3390/s23042270}
}RIS
TY - JOUR TI - A Low-Power Wireless System for Predicting Early Signs of Sudden Cardiac Arrest Incorporating an Optimized CNN Model Implemented on NVIDIA Jetson. AU - Kota VD AU - Sharma H AU - Albert MV AU - Mahbub I AU - Mehta G AU - Namuduri K PY - 2023 JO - Sensors (Basel, Switzerland) DO - 10.3390/s23042270 UR - https://doi.org/10.3390/s23042270 ER -
APA
VD, K., H, S., MV, A., I, M., G, M., & K, N. (2023). A Low-Power Wireless System for Predicting Early Signs of Sudden Cardiac Arrest Incorporating an Optimized CNN Model Implemented on NVIDIA Jetson.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s23042270
Source records
- pubmed · retrieved 2026-09-25T07:16:25.437Z