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...

詳細記述

書誌詳細
主要な著者: Figueredo-Ávila, Gustavo Andrés, Ballesteros-Ricaurte, Javier Antonio
フォーマット: Online
言語:spa
出版事項: Universidad Pedagógica y Tecnológica de Colombia 2016
主題:
オンライン・アクセス:https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/4811
その他の書誌記述
要約: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.