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In this paper, we propose a recommendation method for food intake order based on the glycemic index (GI) using deep learning to reduce rapid blood sugar spikes during meals. The foods in a captured image are classified through a food detection network. The GIs for the detected foods are found by matching their names or categories with the information stored in the database. If the detected food name or category is not found in the database, the food information is found from a public API. The food is classified into one of the food categories based on nutrients, and the median GI of the corresponding category is assigned to the food. The food intake order is recommended from the lowest to the highest GI. We implemented a web service that visualizes the food analysis results and the recommended food intake order. In experimental results, the average inference time and accuracy were 57.1 ms and 98.99% for Mask R-CNN, respectively, and 24.4 ms and 91.72% for YOLOv11, respectively.
Lee, J.-y.; Kwon, S.-k.
Recommendation Method Based on Glycemic Index for Intake Order of Foods Detected by Deep Learning. Electronics2025, 14, 457.
https://doi.org/10.3390/electronics14030457
AMA Style
Lee J-y, Kwon S-k.
Recommendation Method Based on Glycemic Index for Intake Order of Foods Detected by Deep Learning. Electronics. 2025; 14(3):457.
https://doi.org/10.3390/electronics14030457
Chicago/Turabian Style
Lee, Jae-young, and Soon-kak Kwon.
2025. "Recommendation Method Based on Glycemic Index for Intake Order of Foods Detected by Deep Learning" Electronics 14, no. 3: 457.
https://doi.org/10.3390/electronics14030457
APA Style
Lee, J.-y., & Kwon, S.-k.
(2025). Recommendation Method Based on Glycemic Index for Intake Order of Foods Detected by Deep Learning. Electronics, 14(3), 457.
https://doi.org/10.3390/electronics14030457
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
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Lee, J.-y.; Kwon, S.-k.
Recommendation Method Based on Glycemic Index for Intake Order of Foods Detected by Deep Learning. Electronics2025, 14, 457.
https://doi.org/10.3390/electronics14030457
AMA Style
Lee J-y, Kwon S-k.
Recommendation Method Based on Glycemic Index for Intake Order of Foods Detected by Deep Learning. Electronics. 2025; 14(3):457.
https://doi.org/10.3390/electronics14030457
Chicago/Turabian Style
Lee, Jae-young, and Soon-kak Kwon.
2025. "Recommendation Method Based on Glycemic Index for Intake Order of Foods Detected by Deep Learning" Electronics 14, no. 3: 457.
https://doi.org/10.3390/electronics14030457
APA Style
Lee, J.-y., & Kwon, S.-k.
(2025). Recommendation Method Based on Glycemic Index for Intake Order of Foods Detected by Deep Learning. Electronics, 14(3), 457.
https://doi.org/10.3390/electronics14030457
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
