A Dataset of Food Intake Activities Using Sensors with Heterogeneous Privacy Sensitivity Levels

Author:

Wu Yi-Hung1ORCID,Chiang Hsin-Che1ORCID,Shirmohammadi Shervin2ORCID,Hsu Cheng-Hsin1ORCID

Affiliation:

1. National Tsing Hua University, Hsin-Chu, Taiwan

2. University of Ottawa, Ottawa, Canada

Publisher

ACM

Reference37 articles.

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2. 2018. Accessing RS options in pyrealsense2 ̇ Issue #1011 ̇ IntelRealSense/librealsense ̇ GitHub. https://github.com/IntelRealSense/librealsense/issues/1011 2018. Accessing RS options in pyrealsense2 ̇ Issue #1011 ̇ IntelRealSense/librealsense ̇ GitHub. https://github.com/IntelRealSense/librealsense/issues/1011

3. 2023. Telehealth Market Size Share & Trends Analysis Report. https://www.grandviewresearch.com/industry-analysis/telehealth-market-report 2023. Telehealth Market Size Share & Trends Analysis Report. https://www.grandviewresearch.com/industry-analysis/telehealth-market-report

4. 2023. Weight Loss and Diet Management Market. https://www.marketdataforecast.com/market-reports/weight-loss-and-diet-management-market 2023. Weight Loss and Diet Management Market. https://www.marketdataforecast.com/market-reports/weight-loss-and-diet-management-market

5. Recognition of dietary activity events using on-body sensors

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1. Federated Learning Using Multi-Modal Sensors with Heterogeneous Privacy Sensitivity Levels;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-08-05

2. MilliNoise;Proceedings of the ACM Multimedia Systems Conference 2024 on ZZZ;2024-04-15

3. Memory-Efficient High-Accuracy Food Intake Activity Recognition with 3D mmWave Radars;Proceedings of the 8th International Workshop on Multimedia Assisted Dietary Management;2023-10-29

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