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An automated deep learning pipeline generates spatially explicit flower abundance maps from drone images, meeting or exceeding the accuracy of manual counting for some species. The Faster R-CNN model was trained and evaluated on data from five flights across two grassland sites. Precision and recall for some flower types are close to or higher than 90%, though performance varies by species.
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