Self-Configuring CVS to Discriminate Rocket Leaves According to Cultivation Practices and to Correctly Attribute Visual Quality Level

Self-Configuring CVS to Discriminate Rocket Leaves According to Cultivation Practices and to Correctly Attribute Visual Quality Level

Computer Vision Systems (CVS) represent a contactless and non-destructive tool to evaluate and monitor the quality of fruits and vegetables. This research paper proposes an innovative CVS, using a Random Forest model to automatically select the relevant features for classification, thereby avoiding...

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Bibliographic Details
Main Authors:	Michela Palumbo, Bernardo Pace, Maria Cefola, Francesco Fabiano Montesano, Francesco Serio, Giancarlo Colelli, Giovanni Attolico
Format:	Article
Language:	English
Published:	MDPI AG 2021-07-01
Series:	Agronomy
Subjects:	<i>Diplotaxis tenuifolia</i> L. automatic configuration of the CVS color correction models non-destructive contactless quality evaluation fertilization and irrigation recognition from digital images
Online Access:	https://www.mdpi.com/2073-4395/11/7/1353

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