Optimized Transfer Learning for Chlorophyll Content Estimations across Datasets of Different Species...
Optimized Transfer Learning for Chlorophyll Content Estimations across Datasets of Different Species Using Sun-Induced Chlorophyll Fluorescence and Reflectance
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Basel: MDPI AG
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English
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Basel: MDPI AG
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Remote sensing-based techniques have been widely used for chlorophyll content (Cab) estimations, while they are challenging when transferred across different species. Sun-induced chlorophyll fluorescence (SIF) provides a new approach to address these issues. This research explores whether SIF has transferability for Cab estimation and to enhance be...
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Full title
Optimized Transfer Learning for Chlorophyll Content Estimations across Datasets of Different Species Using Sun-Induced Chlorophyll Fluorescence and Reflectance
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TN_cdi_doaj_primary_oai_doaj_org_article_0b7894c8ae4c4c478839ceb2d472c011
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_0b7894c8ae4c4c478839ceb2d472c011
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ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs16111869
