Deep Learning Approaches for Automatic Livestock Detection in UAV Imagery: State-of-the-Art and Future Directions.
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| Title: | Deep Learning Approaches for Automatic Livestock Detection in UAV Imagery: State-of-the-Art and Future Directions. |
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| Authors: | Adam, Muhammad1 (AUTHOR), Song, Jianchao1 (AUTHOR), Yu, Wei1 (AUTHOR), Li, Qingqing1 (AUTHOR) qingqingli@towson.edu |
| Source: | Future Internet. Sep2025, Vol. 17 Issue 9, p431. 20p. |
| Database: | Academic Search Ultimate |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: asn DbLabel: Academic Search Ultimate An: 188278578 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/fi17090431 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 20 StartPage: 431 Titles: – TitleFull: Deep Learning Approaches for Automatic Livestock Detection in UAV Imagery: State-of-the-Art and Future Directions. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Adam, Muhammad – PersonEntity: Name: NameFull: Song, Jianchao – PersonEntity: Name: NameFull: Yu, Wei – PersonEntity: Name: NameFull: Li, Qingqing IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 19995903 Numbering: – Type: volume Value: 17 – Type: issue Value: 9 Titles: – TitleFull: Future Internet Type: main |
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