FCA-YOLO: An Efficient Deep Learning Framework for Real-Time Monitoring of Stored-Grain Pests in Smart Warehouses
Stored wheat pests threaten food quality and economic returns, yet existing detection methods struggle with small-object detection, complex scenarios, and efficiency–accuracy trade-offs, largely due to the lack of high-quality datasets. To address these challenges, this study constructed MPest3 data...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Agronomy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4395/15/6/1313 |
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