AI and Drones Team Up to Track Rice Growth Across Hundreds of Varieties
· newswise.com · popularity 17/100 · 0 similar stories today · Machine Learning Research (Artificial Intelligence)
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Summary
<img src="https://www.newswise.com/legacy/image.php?image=/images/uploads/2026/10/27/1.jpg&width=100&height=150" alt="Newswise image" />A new multi-scale deep-learning framework combines high-frequency medium-resolution drone imagery with sparse high-resolution images to identify rice growth stages across hundreds of genetically diverse varieties. By introducing a Missing-Aware Gated Fusion (MAGF) mechanism, the model handles irregular sampling and phenological asynchrony, where different cultivars reach the same stage on different dates. Validated on more than 100,000 images covering roughly 500 rice cultivars over two growing seasons, the approach achieved an overall accuracy (OA) and F1-score of 0.873, with a Kappa coefficient of 0.84, while sharply reducing the drone flight time needed for high-resolution monitoring.
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