Object Detection on PCB surface-defect dataset
95.84mAP@0.5YOLOX-S
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| YOLOX-SBackbone=DarkNet-532026.03 | 95.84 | 62.03 | 87.16 | 93.73 | 91 | |
| YOLOR-P62026.03 | 94.7 | 54.5 | 93.1 | 93.1 | 94 | |
| DS-MoEBackbone=DS-MoE2026.03 | 94.24 | 53.36 | 83.38 | 96.8 | 89 | |
| AirDet-SBackbone=RepResNet2026.03 | 94.1 | 51.81 | 82.91 | 95.45 | 89 | |
| PP-YOLOE-SBackbone=CSPNet2026.03 | 93.44 | 53.11 | 81.4 | 93.31 | 87 | |
| YOLOv8Backbone=C2f2026.03 | 93.25 | 51.35 | 81.93 | 95.21 | 86 | |
| MLLABackbone=MLLA2026.03 | 93.19 | 51.71 | 82.74 | 95.18 | 86 | |
| YOLOv7Backbone=RepVGG2026.03 | 93.11 | 52.39 | 85.12 | 94.68 | 89 | |
| PromptDetBackbone=CLIP-R502026.03 | 93.1 | 51.8 | 82.9 | 94.5 | 89 | |
| SegMANBackbone=SegMAN2026.03 | 92.21 | 50.46 | 80.32 | 95.52 | 88 | |
| MViTv2-BBackbone=MViTv22026.03 | 92.13 | 51.56 | 81.21 | 95.44 | 89 | |
| YOLOv5-XBackbone=CSPDarkNet2026.03 | 91.8 | 50.7 | 95.2 | 91.3 | 93 | |
| MiniGPT-VBackbone=Phi-2 + ViT-B2026.03 | 91.5 | 50.1 | 82.3 | 93.1 | 89 | |
| YOLOv6-SBackbone=ELAN-Net2026.03 | 91.42 | 49.44 | 84.12 | 95.31 | 89 | |
| YOLOv5-SBackbone=CSPDarkNet2026.03 | 91.2 | 51.8 | 81.82 | 92.12 | 86 | |
| YOLOv4Backbone=CSPDarkNet-532026.03 | 81.2 | 50.06 | 89.37 | 94.78 | 92 | |
| Faster-R-CNNBackbone=ResNet-502026.03 | 78.33 | 50.24 | 67.74 | 74.51 | 70 | |
| YOLOv3Backbone=DarkNet-532026.03 | 73.32 | 47.5 | 90.85 | 52.66 | 67 | |
| EfficientDet-D3Backbone=EfficientNet-B32026.03 | 71.8 | 35 | 99.44 | 49.51 | 66 | |
| CenterNetBackbone=Hourglass-1042026.03 | 43.4 | 14.53 | 43.79 | 52.2 | 48 | |
| SSDBackbone=VGG-162026.03 | 17.1 | 10 | 19.93 | 54.64 | 29 | |
| RetinaNetBackbone=ResNet-1012026.03 | 13.18 | 5 | 66.67 | 4.31 | 8 |