Applying Deep Learning to Track Food Consumption and Human Activity for Non-intrusive Blood Glucose Monitoring-Reference-Cited by-同舟云学术

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Applying Deep Learning to Track Food Consumption and Human Activity for Non-intrusive Blood Glucose Monitoring

Published:2021-12-01 Issue: Volume: Page:
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Container-title:2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)
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Author:

Samir Mohamed Amr,Mohamed Zeinab A.,Hussein Mona Abdelmotaleb A.,Atia Ayman

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9666478/9666481/09666662.pdf?arnumber=9666662

Reference26 articles.

1. iHear Food: Eating Detection Using Commodity Bluetooth Headsets

2. Food Image Classification with Deep Features;?engür;2019 International Artificial Intelli-gence and Data Processing Symposium (IDAP),2019

3. Food Image Classification with Convolutional Neural Network

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Impact of Diet and Nutritional Factors in Controlling Type 2 Diabetes Through Machine Learning;2023 International Conference on Next Generation Electronics (NEleX);2023-12-14

2. Minimally invasive electrochemical continuous glucose monitoring sensors: Recent progress and perspective;Biosensors and Bioelectronics;2023-04

3. Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection;Frontiers in Bioengineering and Biotechnology;2022-05-12

4. Internet of Things based Real-Time Hyperglycemia and Hypoglycemia Monitoring using Wearable Biosensors;2022 International Conference on Electronics and Renewable Systems (ICEARS);2022-03-16

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