Expanding Applications of TinyML in Versatile Assistive Devices: From Navigation Assistance to Health Monitoring System Using Optimized NASNet-XGBoost Transfer Learning
The healthcare sector receives a considerable amount of unprocessed data from wearable and portable devices. However, traditional cloud-based models used to handle this type of data can pose risks such as exposing sensitive patient data to a network environment and increasing latency due to data sto...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10750799/ |
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