The Food Recognition and Nutrition Assessment from Images Using Artificial Intelligence: A Survey
| Audiencia | Público en general | es_ES |
| Cobertura | México[ 143] | es_ES |
| Fecha de ingreso | 2026-10-05T16:35:01Z | |
| Fecha de publicación | 2022-01-01 | |
| Resumen | There are three basic needs for human living: food, home, and clothes. As a result, food plays a critical part in human life. In today's world, every field achieves some level of accomplishment. We should take food as per our body needs. In recent times, many dangerous diseases have taken place in the human body. During this time, awareness of our health is an essential factor for humans. It is essential to know what we should eat in our diet. This paper explores different methods and datasets for food recognition and nutrition assessment from the images of different foods using artificial intelligence and compares different methods and technologies also. Convolutional Neural Network (CNN) is one of the most successful deep learning algorithms for food recognition. As a finding, several existing models of CNN have been explored with different accuracy and results. | es_ES |
| Doi | https://doi.org/10.1149/10701.3547ecst | es_ES |
| ISBN | 978-160768539-5 | es_ES |
| URI | https://riuat.uat.edu.mx/handle/123456789/6482 | |
| Idioma | Inglés[20] | es_ES |
| Editorial | Institute of Physics | es_ES |
| Relación | ECS Transactions | es_ES |
| URL relacionado | https://doi.org/10.1149/10701.3547ecst | es_ES |
| Derechos | Acceso abierto (Metadatos de producción científica) | es_ES |
| Licencia | http://purl.org/coar/access_right/c_abf2 | es_ES |
| Fuente | ECS Transactions | |
| Palabra clave | Artificial Intelligence | es_ES |
| Palabra clave | CNNs | es_ES |
| Palabra clave | Food Recognition | es_ES |
| Palabra clave | Nutrition Assessment | es_ES |
| Palabra clave | Region Proposal Network | es_ES |
| Título | The Food Recognition and Nutrition Assessment from Images Using Artificial Intelligence: A Survey | es_ES |
| Tipo | Ponencia | es_ES |
| Arbitrado | Ha sido Arbitrado | es_ES |
| Autor | Makwana, Yogeshvari | |
| Autor | Iyer, Sailesh | |
| Autor | Tiwari, Sanju | |
| Autor | Makwana, Yogeshvari | es_ES |
| Autor | Iyer, Sailesh | es_ES |
| Autor | Tiwari, Sanju | es_ES |
| Institución | Universidad Autónoma de Tamaulipas | |
| Institución | Universidad Autónoma de Tamaulipas | es_ES |
| Número | 1 | es_ES |
| Rango de páginas | 3547-3553 | es_ES |
| URL relacionada | https://doi.org/10.1149/10701.3547ecst | |
| Tipo de artículo | Indexado | |
| Tipo de artículo | Indexado | es_ES |
| Volumen | 107 | es_ES |