YOLOv8-GO: A Lightweight Model for Prompt Detection of Foliar Maize Diseases
Disease is one of the primary threats to maize growth. Currently, maize disease detection is mainly conducted in laboratories, making it difficult to promptly respond to diseases. To enable detection in the field, a lightweight model is required. Therefore, this paper proposes a lightweight model, Y...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/21/10004 |
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