From: A generalised approach for high-throughput instance segmentation of stomata in microscope images
Dataset | Quality | Known to model | Num. of stomata | Precision (%) | Recall (%) | F-Score (%) |
---|---|---|---|---|---|---|
Gymnosperm 400× | Med–High | Yes | 944 | 95.87 | 98.41 | 97.12 |
Gymnosperm 100×: low | Low | Yes | 10597 | 98.89 | 91.92 | 95.28 |
Gymnosperm 100×: high | High | Yes | 7713 | 98.15 | 94.30 | 96.18 |
Poplar | High | Yes | 5042 | 98.34 | 96.11 | 97.22 |
Cuticle: low | Low | Partially | 8181 | 93.46 | 73.51 | 82.29 |
Cuticle:Â med | Medium | Partially | 2631 | 94.80 | 89.43 | 92.04 |
Ginkgo | High | Partially | 2802 | 96.02 | 82.65 | 88.84 |
USNM/USBG:Â low | Low | Partially | 2569 | 92.70 | 70.65 | 80.19 |
USNM/USBG:Â med | Medium | Partially | 16083 | 95.20 | 82.31 | 88.30 |
Betula nana | Low–Med | No | 683 | 85.62 | 75.25 | 80.06 |
Eucalyptus | Medium | No | 1088 | 93.22 | 83.46 | 88.07 |
Ferns: low | Low | No | 964 | 78.91 | 51.24 | 62.14 |
Ferns: med | Medium | No | 713 | 90.15 | 74.47 | 81.56 |
Grass | Low–Med | No | 3288 | 85.20 | 55.66 | 67.32 |
UNSW-2019 | Med–High | No | 2242 | 91.53 | 85.77 | 88.56 |
Google Images | Medium | No | 1496 | 97.52 | 76.34 | 85.64 |