TDD-YOLO: A novel model for precise detection of tomato diseases
Zijian Chen, Zhihua Bian, Li Li, Chenxu Dai, Zhanlin Ji, Ivan Ganchev · 2026
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Description
Zijian Chen and colleagues built a computer vision model that spots diseases on tomato plants, work now usually done by slow hand inspection in the field. Diseased spots can be tiny, varied in size, and lost against messy backgrounds of leaves and soil. Their model, TDD-YOLO, upgrades a popular detection system with three changes aimed at exactly those problems.
One module sharpens the texture of faint disease spots, another helps the model link features across the image while ignoring background clutter, and a third handles spots at different scales. Precise, fast detection matters because catching an outbreak days earlier can save a harvest. Models like this are a step toward camera-based crop scouting on farms.
Catalog record
| CREATOR | Zijian Chen, Zhihua Bian, Li Li, Chenxu Dai, Zhanlin Ji, Ivan Ganchev |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 77016 |
| LICENSE | CC_BY |
| RIGHTS | CC BY |
| SOURCE | PLOS |