Non-Invasive Optoelectronic System for Color-Change Detection in Oranges to Predict Ripening by Using Artificial Neural Networks
Author:
Affiliation:
1. Facultad de Ingeniería y Ciencias, Universidad Autónoma de Tamaulipas, Matamoros, Tamaulipas, México
2. Departamento de Electrónica, División de Ingenierías CIS, Comunidad de Palo Blanco, Universidad de Guanajuato, Salamanca, Guanajuato, Mexico
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics
Link
http://xplorestaging.ieee.org/ielx7/4563994/10225446/10254239.pdf?arnumber=10254239
Reference60 articles.
1. Non-invasive, real time in-situ techniques to determine the ripening stage of banana
2. A new approach for visual identification of orange varieties using neural networks and metaheuristic algorithms
3. Changes in color-related compounds in tomato fruit exocarp and mesocarp during ripening using HPLC-APcI+-mass Spectrometry
4. Classification of Bitter Orange Essential Oils According to Fruit Ripening Stage by Untargeted Chemical Profiling and Machine Learning
5. Field-Based Scoring of Soybean Iron Deficiency Chlorosis Using RGB Imaging and Statistical Learning
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