A Machine Learning Approach for Estimating sweetpotato Cultivation Areas in Uganda

cg.authorship.typesCGIAR single centreen
cg.contributor.affiliationInternational Potato Centeren
cg.contributor.initiativeSeed Equal
cg.coverage.countryUganda
cg.coverage.iso3166-alpha2UG
cg.creator.identifierS.Rajendran: 0000-0003-2769-2548en
cg.subject.actionAreaResilient Agrifood Systems
cg.subject.actionAreaGenetic Innovation
cg.subject.cipSWEETPOTATOESen
cg.subject.cipCROP AND SYSTEMS SCIENCES CSSen
cg.subject.cipCLIMATE-SMART AGRICULTUREen
cg.subject.cipFOOD SECURITYen
cg.subject.cipBIGDATAen
cg.subject.impactAreaClimate adaptation and mitigation
cg.subject.impactAreaNutrition, health and food security
cg.subject.sdgSDG 2 - Zero hungeren
cg.subject.sdgSDG 12 - Responsible consumption and productionen
cg.subject.sdgSDG 13 - Climate actionen
cg.subject.sdgSDG 9 - Industry, innovation and infrastructureen
cg.subject.sdgSDG 1 - No povertyen
dc.contributor.authorRajendran, S.en
dc.date.accessioned2025-02-03T16:39:04Zen
dc.date.available2025-02-03T16:39:04Zen
dc.identifier.urihttps://hdl.handle.net/10568/172746
dc.titleA Machine Learning Approach for Estimating sweetpotato Cultivation Areas in Ugandaen
dcterms.accessRightsOpen Access
dcterms.audienceAcademicsen
dcterms.audienceCGIARen
dcterms.audienceDevelopment Practitionersen
dcterms.audienceDonorsen
dcterms.audienceExtensionen
dcterms.audienceFarmersen
dcterms.audienceGeneral Publicen
dcterms.audienceNGOsen
dcterms.audiencePolicy Makersen
dcterms.audienceScientistsen
dcterms.bibliographicCitationRajendran, S. 2024. A Machine Learning Approach for Estimating sweetpotato Cultivation Areas in Uganda. International Potato Center.en
dcterms.extent5 p.en
dcterms.issued2024-12en
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.subjectmachine learningen
dcterms.subjectsweet potatoesen
dcterms.subjectseed systemsen
dcterms.subjectclimate-smart agricultureen
dcterms.typeBrief

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