Object Detection on Rice-Leaf benchmark leaderboard · SOTA2 Research

Object Detection on Rice-Leaf

0.678PrecisionTCLeaf-Net

Evaluation Results

Method	Links
TCLeaf-Net2025.12		0.678	0.536	0.573	0.349	0.599
YOLOv8L2025.12		0.659	0.549	0.566	0.346	0.599
YOLOv5L2025.12		0.648	0.55	0.56	0.326	0.595
YOLOv9C2025.12		0.647	0.553	0.561	0.338	0.596
YOLOv3L2025.12		0.632	0.521	0.536	0.331	0.572
YOLO12X2025.12		0.619	0.545	0.57	0.343	0.58
YOLO12L2025.12		0.613	0.546	0.559	0.34	0.578
YOLO11L2025.12		0.602	0.526	0.54	0.333	0.562
RTDETR-R1012025.12		0.553	0.471	0.47	0.281	0.509
RTDETR-X2025.12		0.55	0.447	0.448	0.278	0.493
YOLOv10L2025.12		0.539	0.486	0.466	0.267	0.511
RTDETR-R502025.12		0.527	0.446	0.452	0.276	0.483
RTDETR-L2025.12		0.521	0.5	0.463	0.288	0.511
YOLOv6L2025.12		0.508	0.464	0.464	0.268	0.485