Food Recognition and Nutritional Apps
Fuente:
arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| _version_ | 1866914969684017152 |
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| author | Rahman, Lubnaa Abdur Papathanail, Ioannis Brigato, Lorenzo Spanakis, Elias K. Mougiakakou, Stavroula |
| author_facet | Rahman, Lubnaa Abdur Papathanail, Ioannis Brigato, Lorenzo Spanakis, Elias K. Mougiakakou, Stavroula |
| contents | Food recognition and nutritional apps are trending technologies that may revolutionise the way people with diabetes manage their diet. Such apps can monitor food intake as a digital diary and even employ artificial intelligence to assess the diet automatically. Although these apps offer a promising solution for managing diabetes, they are rarely used by patients. This chapter aims to provide an in-depth assessment of the current status of apps for food recognition and nutrition, to identify factors that may inhibit or facilitate their use, while it is accompanied by an outline of relevant research and development. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2307_05372 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Food Recognition and Nutritional Apps Rahman, Lubnaa Abdur Papathanail, Ioannis Brigato, Lorenzo Spanakis, Elias K. Mougiakakou, Stavroula Computer Vision and Pattern Recognition Computers and Society Food recognition and nutritional apps are trending technologies that may revolutionise the way people with diabetes manage their diet. Such apps can monitor food intake as a digital diary and even employ artificial intelligence to assess the diet automatically. Although these apps offer a promising solution for managing diabetes, they are rarely used by patients. This chapter aims to provide an in-depth assessment of the current status of apps for food recognition and nutrition, to identify factors that may inhibit or facilitate their use, while it is accompanied by an outline of relevant research and development. |
| title | Food Recognition and Nutritional Apps |
| topic | Computer Vision and Pattern Recognition Computers and Society |
| url | https://arxiv.org/abs/2307.05372 |