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Multi-Class Weed Quantification Based on U-Net Convolutional Neural Networks Using UAV Imagery.

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Title: Multi-Class Weed Quantification Based on U-Net Convolutional Neural Networks Using UAV Imagery.
Authors: Sandoval-Pillajo, Lucía1,2, Pusdá-Chulde, Marco2, Pazos-Morillo, Jorge1,2, Granda-Gudiño, Pedro2, García-Santillán, Iván2, idgarcia@utn.edu.ec
Source: Applied Sciences (2076-3417); Apr2026, Vol. 16 Issue 7, p3149, 26p
Database: Applied Science & Technology Source
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  Data: Multi-Class Weed Quantification Based on U-Net Convolutional Neural Networks Using UAV Imagery.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=192959492
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        Value: 10.3390/app16073149
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      – Code: eng
        Text: English
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        PageCount: 26
        StartPage: 3149
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      – TitleFull: Multi-Class Weed Quantification Based on U-Net Convolutional Neural Networks Using UAV Imagery.
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            NameFull: Sandoval-Pillajo, Lucía
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            NameFull: Pusdá-Chulde, Marco
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              Text: Apr2026
              Type: published
              Y: 2026
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              Value: 16
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