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Freshness and quality assessment of parsley using image processing and artificial intelligence techniques
Provedor de dados: 111
Autores: Hosseinpour Zarnaq, Mohammad; Omid, Mahmoud; Soltani Firouz, Mahmoud; Jafarian, Mostafa; Bazyar, Pourya.
Fruits and&amp;nbsp;vegetables&amp;nbsp;are&amp;nbsp;important&amp;nbsp;components of healthy diets. Vegetable freshness is important for both postharvest industry and consumer appeal. This study focused on freshness detection of parsleys using combined image processing and artificial intelligence techniques. A dataset of color and texture features computed from parsley images. Linear discriminant analysis (LDA) and principal component analysis (PCA) methods are used for feature reduction. Multilayer perceptron (MLP) neural networks, support vector machine (SVM) and decision trees (DTs) classifiers were used for classification. Results showed MLP with LDA feature selection methods had higher performance and the overall accuracy, RMSE, MAE of MLP classifier...
Tipo: Info:eu-repo/semantics/article
Ano: 2022
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/7687