Comparison of SIoU and CIoU loss functions: Classification loss, precision, and mAP50 convergence performance.

Comparison of SIoU and CIoU loss functions: Classification loss, precision, and mAP50 convergence performance.

<p>Comparison of SIoU and CIoU loss functions: Classification loss, precision, and mAP50 convergence performance.</p>

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Bibliographic Details
Main Author:	Weiyu Han (3448742) (author)
Other Authors:	Zixuan Cai (20765907) (author), Xin Li (51274) (author), Anan Ding (20765910) (author), Yuelin Zou (20765913) (author), Tianjun Wang (1524403) (author)
Published:	2025
Subjects:	Medicine Genetics Molecular Biology Sociology Cancer Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified suppress irrelevant features siou loss function simam attention mechanism introducing scconv module improve c2f module higher average accuracy experimental results show encompasses four types target detection dataset low detection accuracy improve detection accuracy distribution network inspections accelerate model convergence insulator dataset compared high model complexity defect detection network insulator defect types defect detection network improves computational complexity shedding insulator model parameters broken insulator absent insulator study propose study creates reduces spatial lightweight algorithm effective solution critical task channel redundancy address issues
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