RGB image-based drought stress classification of garden plants using SVM model
Seong-Ju Lee, Seung-Won Han, Tae-Wan Kim, Sung-Yung Yoo · 2026
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Description
Sorting thirsty garden plants from comfortable ones usually means lab gear, but ordinary photos may suffice. Seong-Ju Lee and co-authors built in 2026 a classifier that reads drought stress from standard color images of ten garden species.
They first grouped plants by measured stress responses, using light-based leaf signals plus image indices. Then they asked whether image indices alone could reproduce the groups. A support vector machine using four predictors, including soil moisture, reached ninety-one percent accuracy, clearly beating a linear rival. The authors frame the method as cheap irrigation guidance for mixed plantings, while noting it still needs field testing.
Catalog record
| CREATOR | Seong-Ju Lee, Seung-Won Han, Tae-Wan Kim, Sung-Yung Yoo |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 58 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |