Metallurgy, Vol. 63 No. 2, 2024.
Original scientific paper
The weld seam detection method based on the infocrnet model
J. P. Hui
; School of Computer Science and Software Engineering, University of Science and Technology Liaoning, China
G. Y. Lian
; School of Artificial Intelligence, Shenzhen Polytechnic University, Shenzhen, China
*
J. S. Wu
; School of Computer Science and Software Engineering, University of Science and Technology Liaoning, China
* Corresponding author.
Abstract
Weld seam detection is particularly crucial within industrial systems, as it promptly reflects the quality of product fabrication and performance, ensuring the final metallurgical product’s quality while mitigating potential losses stemming from product quality issues. This paper proposed the InfoFPN Cross Refinement Network (InfoCRNet) for the weld seam detection, achieving an accuracy rate of 98,90% and F1 score of 98,85 %.
Keywords
metallurgical production; weld seam detection; InfoCRNet; network model method
Hrčak ID:
312318
URI
Publication date:
1.4.2024.
Visits: 256 *