Towards Explainable Cuisine Prediction for Recipes with Image Color Analysis
Food is an important factor when choosing a touristic destination, and culinary images are a fundamental tool in gastronomic marketing. This paper presents an approach to analyse the use of color in food images based on a dataset of more than 22000 recipes coming form a popular recipe website, inclu...
| Autores: | , , , |
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| Tipo de recurso: | capítulo de libro |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/180100 |
| Acceso en línea: | https://hdl.handle.net/11441/180100 https://doi.org/10.3233/FAIA240444 |
| Access Level: | acceso abierto |
| Palabra clave: | Gastronomy Cuisine of World Natural Language Processing Kruskal- Wallis |
| Sumario: | Food is an important factor when choosing a touristic destination, and culinary images are a fundamental tool in gastronomic marketing. This paper presents an approach to analyse the use of color in food images based on a dataset of more than 22000 recipes coming form a popular recipe website, including images of the final dishes and scores that indicate how well the recipe was valued by users. First, the specific cuisine of each recipe is inferred by using the Llama 3 Large Language Model (LLM). The main color of the dish images is also determined. Fi- nally, statistically significant relationships between scores and cuisine labels is also determined. Our preliminary results show some relevant results for tourist market- ing, such as showing the most popular cuisines. |
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