Análisis Inteligente para el Apoyo a la Inspección Veterinaria en Mataderos Basado en Visión por Computador
DOI:
https://doi.org/10.30681/rbegdr.v8i3.14507Palabras clave:
Inspección Alimentaria, Inteligencia Artificial, Redes Neuronales Convolucionales (CNNs), Redes Neuronales Recurrentes (RNNs), Visión por Computador, Vision Transformers (ViTs)Resumen
"El avance de las tecnologías de inteligencia artificial y visión por computador ha revolucionado los procesos de inspección veterinaria en mataderos, proporcionando mayor precisión, eficiencia y seguridad alimentaria. Este estudio tuvo como objetivo analizar la aplicación integrada de redes neuronales convolucionales (CNNs), redes neuronales recurrentes (RNNs) y Vision Transformers (ViTs) en sistemas inteligentes orientados a la detección de anomalías y al control de calidad. La metodología utilizada fue una revisión integradora, con publicaciones entre 2021 y 2025, en bases científicas. Los resultados indican que la combinación de estas arquitecturas potencia el análisis visual y predictivo, permitiendo decisiones automatizadas más fiables y en tiempo real. Se concluye que la integración de las redes neuronales representa una evolución significativa para la modernización de la inspección alimentaria, promoviendo un enfoque proactivo, autónomo y basado en datos."
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