Table 3 Performance comparison of object detection models.

From: YOLO11-WLBS: an efficient model for pavement defect detection

Models

P

R

F1

mAP@0.50

mAP@0.50–0.95

Para/M

SSD

0.572

0.388

0.462

0.531

0.332

32.77

Faster R-CNN

0.636

0.451

0.528

0.598

0.391

26.21

Mask R-CNN

0.659

0.486

0.560

0.611

0.403

25.32

YOLOv5

0.763

0.524

0.621

0.731

0.549

22.18

YOLOv8

0.823

0.624

0.714

0.775

0.619

23.27

YOLOv9

0.832

0.625

0.714

0.765

0.613

16.78

YOLOv10

0.831

0.632

0.718

0.769

0.596

16.58

YOLO11

0.853

0.698

0.768

0.797

0.624

20.06

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