Ablation experiment results.

<div><p>The background of pipeline weld surface defect image is complex, and the defect size is small. Aiming at the small defect size in the weld image, which is easy to cause missed detection and false detection, a lightweight target detection algorithm based on improved YOLOv7 is prop...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Xiangqian Xu (17310895) (author)
مؤلفون آخرون:	Wenting Hou (1995478) (author), Xing Li (134367) (author)
منشور في:	2024
الموضوعات:	Medicine Sociology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified loss function ciou less computational overhead href =" mailto experimental results show eiou loss function depthwise separable convolution 3 %, respectively feature fusion network div >< p cause missed detection small size defects small defect size model calculation amount improved yolov7 algorithm defect size network calculation parameter amount improved yolov7 convolution module 2 %, backbone network detect small defect images defect detection weld image sized targets reach 72 parameter quantity model volume high degree false detection effectively reduce effectively applied detection method detection ability convergence speed completely detect
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Ablation experiment results.

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