TY - JOUR
T1 - CLASSIFICATION OF APPLES WITH CONVOLUTIONAL NEURONAL NETWORKS
AU - Olguín-Rojas, Juan C.
AU - Vasquez-Gomez, Juan I.
AU - López-Canteñs, Gilberto de J.
AU - Herrera-Lozada, Juan C.
N1 - Publisher Copyright:
© 2022, Revista Fitotecnia Mexicana.All Rights Reserved.
PY - 2022
Y1 - 2022
N2 - Nowadays, in points of sale and in agro-industrial companies in Mexico, the classification of apples (Malus domestica) is carried out manually by people, which generates deficiencies in the quality of the product. These problems can be reduced with the implementation of in site vision equipment with machine learning algorithms. In this study, several convolutional neuronal network (CNN) architectures were analyzed and one of those was selected that allows apples to be classified into healthy and damaged in the postharvest process. The varieties used were Red Delicious, Granny Smith, Golden Delicious and Gala. The accuracy of the LeNet5 and VGG16 CNNs was compared. A series of treatments (combination of network with hyperparameters) was performed that were used for the classification of the object of study. As each treatment was tested, its performance was measured.
AB - Nowadays, in points of sale and in agro-industrial companies in Mexico, the classification of apples (Malus domestica) is carried out manually by people, which generates deficiencies in the quality of the product. These problems can be reduced with the implementation of in site vision equipment with machine learning algorithms. In this study, several convolutional neuronal network (CNN) architectures were analyzed and one of those was selected that allows apples to be classified into healthy and damaged in the postharvest process. The varieties used were Red Delicious, Granny Smith, Golden Delicious and Gala. The accuracy of the LeNet5 and VGG16 CNNs was compared. A series of treatments (combination of network with hyperparameters) was performed that were used for the classification of the object of study. As each treatment was tested, its performance was measured.
KW - Classification
KW - Lenet5
KW - Malus domestica
KW - Vgg16
UR - http://www.scopus.com/inward/record.url?scp=85138157621&partnerID=8YFLogxK
U2 - 10.35196/rfm.2022.3.369
DO - 10.35196/rfm.2022.3.369
M3 - Artículo
AN - SCOPUS:85138157621
SN - 0187-7380
VL - 45
SP - 369
EP - 378
JO - Revista Fitotecnia Mexicana
JF - Revista Fitotecnia Mexicana
IS - 3
ER -