Comparison of SCP-DETR and other models on the PKU-Market-PCB dataset during training in terms of mAP@0.5 (left) and mAP@0.5:0.95 (right).

Comparison of SCP-DETR and other models on the PKU-Market-PCB dataset during training in terms of mAP@0.5 (left) and mAP@0.5:0.95 (right).

<p>Comparison of SCP-DETR and other models on the PKU-Market-PCB dataset during training in terms of mAP@0.5 (left) and mAP@0.5:0.95 (right).</p>

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Yuanyuan Wang (20181) (author)
مؤلفون آخرون: Tongtong Yin (14758525) (author), Xiuchuan Chen (22146211) (author), Yemeng Zhu (22146214) (author), Jibin Wang (373893) (author), Yonghao Ma (554708) (author), Luyue Liu (22146217) (author), Jiajun Wang (512021) (author)
منشور في: 2025
الموضوعات:
Neuroscience
Sociology
Space Science
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Chemical Sciences not elsewhere classified
Information Systems not elsewhere classified
storage seriously impact
s3 feature layer
s2 feature layer
recently released yolov11m
holds significant implications
excessive background interference
improves detection capability
neck feature fusion
ultimately enhancing small
shaped convolution ),
4 %, representing
subtle small targets
specially designed co
proposed method achieves
original fusion module
experimental results demonstrate
div >< p
target detection performance
pcb defect detection
method improves map
results demonstrate
proposed method
fusion module
defect targets
detection accuracy
small size
pcb manufacturing
efficient small
depth convolution
3 %,
proposed cspokm
kernel module
use spdconv
superior performance
paper proposes
local scales
limited due
industrial production
electronic components
downsampling operations
defects generated
csp omni
computational complexity
better accommodates
6 %.
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