Computer vision applied to food and agricultural products
Computer vision (CV) applies to many human activities, and its application is a decisive key for the agri-food industry as it progresses towards Industry 4.0. In the agricultural field, CV systems are applied to seeding, cultivation, farm management, disease control, weed control, robotic harvesting...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | Brasil |
| Institución: | Universidade Federal do Ceará (UFC) |
| Repositorio: | Revista ciência agronômica (Online) |
| Idioma: | inglés |
| OAI Identifier: | oai:periodicos.ufc:article/84918 |
| Acceso en línea: | http://periodicos.ufc.br/revistacienciaagronomica/article/view/84918 |
| Access Level: | acceso abierto |
| Palabra clave: | Digital images Machine vision Agriculture 4.0 Machine learning Artificial intelligence |
| Sumario: | Computer vision (CV) applies to many human activities, and its application is a decisive key for the agri-food industry as it progresses towards Industry 4.0. In the agricultural field, CV systems are applied to seeding, cultivation, farm management, disease control, weed control, robotic harvesting, post-harvest control, quality assessment, composition analysis, sorting, and classification. Therefore, the coupling of CV systems, data from new sensors, and artificial intelligence tools such as machine learning and deep learning can enable the automatic management of many tasks previously depended on humans. Thus, the aim of this paper is to review the state-of-the-art CV applied to food and agricultural products. |
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