Optimizing Corn Tar Spot Measurement : A Deep Learning Approach Using Red-Green-Blue Imaging and Stromata Contour Detection Algorithm for Leaf-Level Disease Severity Analysis
Visual detection of stromata (brown-black, elevated fungal fruiting bodies) is a primary method for quantifying tar spot early in the season, as these structures are definitive signs of the disease and essential for effective disease monitoring and management. Here, we present Stromata Contour Detec...
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Bibliographische Detailangaben
| Veröffentlicht in: | Plant disease. - 1997. - (2024) vom: 19. Aug.
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| 1. Verfasser: |
Lee, Da-Young
(VerfasserIn) |
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| Weitere Verfasser: |
Na, Dong-Yeop,
Gongora-Canul, Carlos,
Jimenez-Beitia, Fidel,
Goodwin, Stephen,
Cruz, Andres,
Delp, Edward J,
Acosta, Alex G,
Lee, Jeong-Soo,
Falconi, Cesar Eduardo,
Cruz, Christian D |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | Plant disease
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| Schlagworte: | Journal Article
Convolutional Neural Network (CNN)
Plant disease phenotyping
Tar spot of corn |
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