A Food Recommender Based on Frequent Sets of Food Mining Using Image Recognition
Food recommendation is an important service in our life. To set a system, we searched a set of food images from social network which were shared or reviewed on the web, including the information that people actually chose in daily life. In the field of representation learning, we proposed a scalable...
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| Autores principales: | , , , |
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| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2021
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| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/76180 |
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| Sumario: | Food recommendation is an important service in our life. To set a system, we searched a set of food images from social network which were shared or reviewed on the web, including the information that people actually chose in daily life. In the field of representation learning, we proposed a scalable architecture for integrating different deep neural networks (DNNs) with a reliability score of DNN. This allowed the integrated DNN to select a suitable recognition result obtained from the different DNNs that were independently constructed. The frequent set of foods extracted from food images was applied to Apriori data mining algorithm for the food recommendation process. In this study, we evaluated the feasibility of our proposed method. |
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| ISBN: | 978-1-83962-387-5 |
| DOI: | 10.5772/intechopen.97186 |