Factors affecting deep learning model performance in citizen science–based image data collection for agriculture: A case study on coffee crops
| cg.authorship.types | CGIAR and advanced research institute | en |
| cg.contributor.affiliation | International Center for Tropical Agriculture | en |
| cg.contributor.affiliation | Leibniz Centre for Agricultural Landscape Research (ZALF) | en |
| cg.contributor.affiliation | Brandenburg University of Technology Cottbus-Senftenberg | en |
| cg.creator.identifier | Juan Camilo Rivera-Palacio: 0000-0002-1423-3396 | |
| cg.creator.identifier | Christian Bunn: 0000-0003-2175-8745 | |
| cg.creator.identifier | Masahiro Ryo: 0000-0002-5271-3446 | |
| cg.identifier.doi | https://doi.org/10.1016/j.compag.2025.110096 | en |
| cg.isijournal | ISI Journal | en |
| cg.issn | 0168-1699 | en |
| cg.journal | Computers and Electronics in Agriculture | en |
| cg.reviewStatus | Peer Review | en |
| cg.subject.alliancebiovciat | INFORMATICS | en |
| cg.subject.alliancebiovciat | INFORMATION SYSTEMS | en |
| cg.subject.alliancebiovciat | RESILIENCE | en |
| cg.subject.alliancebiovciat | SMALLHOLDER FARMERS | en |
| cg.subject.alliancebiovciat | VALUE CHAINS | en |
| cg.subject.sdg | SDG 2 - Zero hunger | en |
| cg.subject.sdg | SDG 13 - Climate action | en |
| cg.volume | 232 | en |
| dc.contributor.author | Rivera-Palacio, Juan Camilo | en |
| dc.contributor.author | Bunn, Christian | en |
| dc.contributor.author | Ryo, Masahiro | en |
| dc.date.accessioned | 2025-02-18T12:43:12Z | en |
| dc.date.available | 2025-02-18T12:43:12Z | en |
| dc.identifier.uri | https://hdl.handle.net/10568/173163 | |
| dc.title | Factors affecting deep learning model performance in citizen science–based image data collection for agriculture: A case study on coffee crops | en |
| dcterms.accessRights | Open Access | |
| dcterms.bibliographicCitation | Rivera-Palacio, J.C.; Bunn, C.; Ryo, M. (2025) Factors affecting deep learning model performance in citizen science–based image data collection for agriculture: A case study on coffee crops. Computers and Electronics in Agriculture 232: 110096. ISSN: 0168-1699 | en |
| dcterms.extent | 110096 | en |
| dcterms.issued | 2025-02-13 | |
| dcterms.language | en | |
| dcterms.license | CC-BY-4.0 | |
| dcterms.publisher | Elsevier BV | en |
| dcterms.subject | machine learning | en |
| dcterms.subject | coffee | en |
| dcterms.subject | vision | en |
| dcterms.type | Journal Article |
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