Máquinas que aprenden por sí solas. De esto va la rama de la inteligencia artificial conocida como “Machine Learning”. En AINIA ya estamos aplicándola a sistemas de control de calidad y seguridad alimentaria, desde el control de placas Petri en laboratorios de análisis de alimentos, al análisis de datos para optimizar procesos productivos en la industria. En el artículo damos las claves.
La complejidad de los productos y los procesos de fabricación de la industria alimentaria, así como el volumen y disparidad de datos que se generan, obligan a avanzar de forma decidida en la aplicación de técnicas de aprendizaje automático (“Machine Learning”) para extraer información que ayude a la toma de decisiones.
Este tipo de técnicas permite clasificar las ingentes cantidades de información de datos en tiempo real y, por lo tanto, utilizar al máximo el potencial de la industria 4.0. Si entrenamos a las máquinas para que, al igual que los sistemas neuronales, resuelvan problemas complejos como la detección de defectos o la identificación de patrones en tiempo real, las potencialidades del procesamiento digital de imágenes son inmensas.
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