Machine Learning-Based Approaches for Predicting SPAD Values of Maize Using Multi-Spectral Images
Machine Learning-Based Approaches for Predicting SPAD Values of Maize Using Multi-Spectral Images
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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Contents
Precisely monitoring the growth condition and nutritional status of maize is crucial for optimizing agronomic management and improving agricultural production. Multi-spectral sensors are widely applied in ecological and agricultural domains. However, the images collected under varying weather conditions on multiple days show a lack of data consiste...
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Full title
Machine Learning-Based Approaches for Predicting SPAD Values of Maize Using Multi-Spectral Images
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TN_cdi_doaj_primary_oai_doaj_org_article_0a42d0dab8ee43f3aa19c355996a3fe9
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_0a42d0dab8ee43f3aa19c355996a3fe9
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ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs14061337
