Machine Learning Methods for Automatic Segmentation of Images of Field- and Glasshouse-Based Plants for High-Throughput Phenotyping

Machine Learning Methods for Automatic Segmentation of Images of Field- and Glasshouse-Based Plants for High-Throughput Phenotyping

Image segmentation is a fundamental but critical step for achieving automated high- throughput phenotyping. While conventional segmentation methods perform well in homogenous environments, the performance decreases when used in more complex environments. This study aimed to develop a fast and robust...

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Bibliographic Details
Main Authors: Frank Gyan Okyere, Daniel Cudjoe, Pouria Sadeghi-Tehran, Nicolas Virlet, Andrew B. Riche, March Castle, Latifa Greche, Fady Mohareb, Daniel Simms, Manal Mhada, Malcolm John Hawkesford
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Plants
Subjects:
feature extraction
imaging
machine learning
phenotyping
segmentation
Online Access:https://www.mdpi.com/2223-7747/12/10/2035

Internet

https://www.mdpi.com/2223-7747/12/10/2035

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