Table 10 Metrics for each pathology type (YOLOv11l-seg)
From: Deep learning-driven pathology detection and analysis in historic masonry buildings of Suzhou
Class | Images | Instances | Box | Mask | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
Precision | Recall | mAP50 | mAP50-95 | Precision | Recall | mAP50 | mAP50-95 | |||
all | 174 | 1963 | 0.547 | 0.475 | 0.519 | 0.305 | 0.596 | 0.451 | 0.499 | 0.29 |
ML | 3 | 23 | 0.682 | 0.652 | 0.782 | 0.458 | 0.761 | 0.691 | 0.806 | 0.532 |
DD | 148 | 1001 | 0.535 | 0.46 | 0.502 | 0.348 | 0.561 | 0.412 | 0.484 | 0.306 |
CR | 59 | 144 | 0.44 | 0.486 | 0.464 | 0.263 | 0.486 | 0.473 | 0.471 | 0.202 |
SS | 137 | 746 | 0.543 | 0.492 | 0.515 | 0.35 | 0.605 | 0.475 | 0.516 | 0.331 |
BI | 20 | 49 | 0.535 | 0.286 | 0.331 | 0.108 | 0.569 | 0.204 | 0.218 | 0.0788 |
