Implementaciones de selección visual en frutas: revisión sistemática de literatura

Autores/as

DOI:

https://doi.org/10.51252/rcsi.v4i1.591

Palabras clave:

agrícola, algoritmos, dispositivos informáticos, frutos, reconocimiento de imágenes, visión artificial

Resumen

La visión artificial tiene una participación importante en el sector agrícola debido a las soluciones que proporciona mediante el reconocimiento de imágenes de frutos considerando su color y forma. El problema es la dificultad en la evaluación de la calidad del fruto, siendo realizado por personas, se cometen errores al realizar la selección manual, ya que se involucra el aspecto subjetivo y sus capacidades de percepción. Siendo necesario implementar sistemas de este tipo, se desarrolló una revisión sistemática de literatura utilizando la metodología PRISMA, el cual busca identificar los algoritmos, modelos, dispositivos informáticos, librerías o software vigentes que son utilizados en implementaciones de visión artificial para la fruta. Los resultados evidencian 32 algoritmos, 32 equipamientos informáticos, 25 modelos, 8 librerías o software que posibilita la realización de implementaciones para la selección visual. En síntesis, la visión artificial impacta significativamente en la selección y clasificación de frutas al mejorar la eficiente, reducir el trabajo manual y acelerar el tiempo de selección. Este avance no solo contribuye la agricultura precisa, sino que también promueve la sostenibilidad al optimizar los procesos y mejorar la calidad de productos, obteniendo un importante en la unión de la tecnología con la agricultura.

Citas

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RCSI

Publicado

2024-01-10

Cómo citar

Parraga-Badillo, S. R., & Coral-Ygnacio, M. A. (2024). Implementaciones de selección visual en frutas: revisión sistemática de literatura . Revista Científica De Sistemas E Informática, 4(1), e591. https://doi.org/10.51252/rcsi.v4i1.591