Sugar beet farming goes high-tech: a method for automated weed detection using machine learning and deep learning in precision agriculture.
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| Title: | Sugar beet farming goes high-tech: a method for automated weed detection using machine learning and deep learning in precision agriculture. |
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| Authors: | Ortatas, Fatma Nur1, Ozkaya, Umut2, Sahin, Muhammet Emin1, emin.sahin@bozok.edu.tr, Ulutas, Hasan1 |
| Source: | Neural Computing & Applications; Mar2024, Vol. 36 Issue 9, p4603-4622, 20p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 175529902 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00521-023-09320-3 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 20 StartPage: 4603 Titles: – TitleFull: Sugar beet farming goes high-tech: a method for automated weed detection using machine learning and deep learning in precision agriculture. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ortatas, Fatma Nur – PersonEntity: Name: NameFull: Ozkaya, Umut – PersonEntity: Name: NameFull: Sahin, Muhammet Emin – PersonEntity: Name: NameFull: Ulutas, Hasan IsPartOfRelationships: – BibEntity: Dates: – D: 20 M: 03 Text: Mar2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 09410643 Numbering: – Type: volume Value: 36 – Type: issue Value: 9 Titles: – TitleFull: Neural Computing & Applications Type: main |
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