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Mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean squared error (RMSE) for 10 sets of training images for a sorghum panicle detection and counting algorithm using a U-Net Convolutional Neural Networks model on unmanned aerial system images.
| No. of Images | 100 | 200 | 300 | 400 | 500 | 600 | 700 | 800 | 900 | 1000 |
|---|---|---|---|---|---|---|---|---|---|---|
| MAE | 53.1 | 35.2 | 28.1 | 27.2 | 23.7 | 19.6 | 16.9 | 11.4 | 9.9 | 6.3 |
| MAPE | 0.41 | 0.25 | 0.20 | 0.21 | 0.18 | 0.15 | 0.13 | 0.09 | 0.07 | 0.05 |
| RMSE | 7.3 | 5.9 | 5.3 | 5.2 | 4.9 | 4.4 | 4.1 | 3.4 | 3.2 | 2.5 |
