Fruit rrpeness identification with artificial neural networks - A review

The application of Artificial Neural Networks (ANNs) and artificial vision has received more and more acceptance in the food industry. These techniques prioritize the classification, pattern recognition, and prediction of the harvests and physical changes in the products. In order to understand the impact of these techniques, this article defines the concept of neural network and describes its main characteristics and models; and, on the other hand, defines the concept of digital imagery processing and its different stages, Complementarily, this review presents an overview of fruit inspection (focused on Colombia) and its techniques, and specifies and orders by application area different works in which ANNs techniques and artificial vision have been applied in the food industry. Finally, the impact of both techniques in the classification, pattern recognition and prediction in alimentary products area is conclusively identified.

• Fecha de publicación: 2016
• Institución: Universidad Pedagógica y Tecnológica de Colombia
• Repositorio: RiUPTC: Repositorio Institucional UPTC
• Idioma: spa
• OAI Identifier: oai:repositorio.uptc.edu.co:001/10569
• Acceso en línea: https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/4811; https://repositorio.uptc.edu.co/handle/001/10569
• Palabra clave: artificial neural networks (ANN); food inspection; image processing; recognition of objects.; inspección de alimentos; procesamiento de imágenes; reconocimiento de objetos; Redes Neuronales Artificiales (RNA)
• License: Copyright (c) 2016 CIENCIA Y AGRICULTURA