Computer vision by unsupervised machine learning in seed drying process

ABSTRACT Analyzing the impact of harvest-time drying data is crucial for successful storage and maintaining regulatory seed quality. This study aimed to assess the performance of fixed and mobile dryers using machine learning techniques. Data were collected from convective dryers, including the tota...

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Bibliographische Detailangaben

Hauptverfasser:	Pinheiro, Romário de Mesquita, Gadotti, Gizele Ingrid, Bernardy, Ruan, Tim, Rafael Rico, Pinto, Karine Von Ahn, Buck, Graciela
Format:	Dataset
Sprache:	eng
Schlagworte:	Agricultural Biotechnology not elsewhere classified
Online-Zugang:	Volltext bestellen
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