Testing the suitability of automated machine learning, hyperspectral imaging and CIELAB color space for proximal in situ fertilization level classification

Testing the suitability of automated machine learning, hyperspectral imaging and CIELAB color space for proximal in situ fertilization level classification

Automated machine learning (AutoML) is considered the next advancement in artificial intelligence due to its commitment to delivering high-performance end-to-end machine learning pipelines with minimal user input. Although AutoML has demonstrated significant potential in computer vision tasks, as fa...

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Bibliographic Details
Main Authors: Ioannis Malounas, Diamanto Lentzou, Georgios Xanthopoulos, Spyros Fountas
Format: Article
Language:English
Published: Elsevier 2024-08-01
Series:Smart Agricultural Technology
Subjects:
Hyperspectral Imaging
AutoML
Broccoli
Fertilization
Artificial intelligence
CIELAB color space
Online Access:http://www.sciencedirect.com/science/article/pii/S277237552400042X

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http://www.sciencedirect.com/science/article/pii/S277237552400042X

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