AI-Powered Handheld Device Counts Male and Female Litchi Flowers in the Orchard
· newswise.com · popularity 16/100 · 0 similar stories today · AI & Data Science (Artificial Intelligence)
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Summary
A new deep-learning network can simultaneously identify and count female and male litchi flowers from images, a task that previously required time-consuming manual observation. Named FQGR-Net (Flower Quantification and Gender Recognition Network), the three-branch model produces separate density maps for each flower sex in a single inference pass. On a self-constructed dataset, it achieved average mean absolute error (MAE) of 8.498 and root mean squared error (RMSE) of 13.209 across categories, with coefficients of determination (R²) of 0.930 for female flowers and 0.971 for male flowers. A portable analyzer built around the model reached over 80% counting accuracy in orchard trials.
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