Enhancing smallholder wheat yield prediction through sensor fusion and phenology with machine learning and deep learning methods
Type:
Title:
Enhancing smallholder wheat yield prediction through sensor fusion and phenology with machine learning and deep learning methods
Creator:
Aklilu Tesfaye, A.;
Awoke, B.G.;
Sida, T.S.;
https://orcid.org/0000-0001-6482-2669
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Osgood, D.
Awoke, B.G.;
Sida, T.S.;
Sida, T.S.
https://orcid.org/0000-0001-6482-2669
Scopus ID
Researcher ID
Items in this Repository
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Osgood, D.
Year:
2022
Copyright:
CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
Journal:
Agriculture (Switzerland)
Journal volume:
12
Journal issue:
9
Article number:
1352
Place of Publication:
Basel (Switzerland)
Publisher:
MDPI
