Revolutionizing Coffee Farming: A Mobile App with GPS-Enabled Reporting for Rapid and Accurate On-Site Detection of Coffee Leaf Diseases Using Integrated Deep Learning

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datacite.relatedItem.firstPage146
datacite.relatedItem.issue2
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datacite.relatedItem.relatedItemIdentifier2674-113X
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datacite.relatedItem.titleSoftware
datacite.relatedItem.volume3
dc.contributor.authorEric Hitimana
dc.contributor.authorMartin Kuradusenge
dc.contributor.authorOmar Janvier Sinayobye
dc.contributor.authorChrysostome Ufitinema
dc.contributor.authorJane Mukamugema
dc.contributor.authorTheoneste Murangira
dc.contributor.authorEmmanuel Masabo
dc.contributor.authorPeter Rwibasira
dc.contributor.authorDiane Aimee Ingabire
dc.contributor.authorSimplice Niyonzima
dc.contributor.authorGaurav Bajpai
dc.contributor.authorSimon Martin Mvuyekure
dc.contributor.authorJackson Ngabonziza
dc.date.accessioned2024-08-14T11:15:47Z
dc.date.available2024-08-14T11:15:47Z
dc.date.issued2024
dc.identifier.doihttps://doi.org/10.3390/software3020007
dc.identifier.otherjz000088-0005
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/3762
dc.publisherMDPI AG
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc004
dc.titleRevolutionizing Coffee Farming: A Mobile App with GPS-Enabled Reporting for Rapid and Accurate On-Site Detection of Coffee Leaf Diseases Using Integrated Deep Learning
dc.typeArticle
dcat.distribution.pdfhttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/3763
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