A Low-Power Wireless System for Predicting Early Signs of Sudden Cardiac Arrest Incorporating an Optimized CNN Model Implemented on NVIDIA Jetson.

Kota VD, Sharma H, Albert MV, Mahbub I, Mehta G, Namuduri K

Open source

DOI
10.3390/s23042270
Published
2023 Feb 17
Container
Sensors (Basel, Switzerland)
Publisher
Not recorded
Open access
yes

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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

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