A comprehensive review of deep learning approaches for rice disease detection: Datasets, methodologies, and future directions
As a staple food for the majority of the global population, rice plays a vital role in food security. However, rice crop yield is heavily influenced by factors such as soil quality, weather, irrigation, and biological threats like pathogens (fungi, bacteria, viruses). Traditional methods for detecti...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Smart Agricultural Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375525002096 |
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