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SFP-YOLO: An infrared image detection algorithm for steel plate welding defects | Synapse
March 3, 2026
SFP-YOLO: An infrared image detection algorithm for steel plate welding defects
YL
Yanfeng Li
Guangdong Polytechnic Normal University
YL
Yongbiao Luo
Guangdong Polytechnic Normal University
CX
Chunmei Xu
Southwest University of Science and Technology
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Key Points
Detection algorithm identifies welding defects effectively through infrared imaging and deep learning techniques.
The algorithm shows an accuracy rate of over 90% in detecting defects within steel plates.
Analysis involved computer vision methods applied to infrared images of welding sites.
The findings highlight the potential to enhance industrial quality control through advanced imaging techniques.
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Li et al. (Sun,) studied this question.
synapsesocial.com/papers/69a7655cbadf0bb9e87d8d27
https://doi.org/https://doi.org/10.1016/j.infrared.2026.106430