Lightweight YOLO-Driven Architecture for On-Line Cup Rupture Detection in Strip Steel Welds

Published: 25 July 2025| Version 1 | DOI: 10.17632/8cdkzy638x.1
Contributor:
Shuai Zhao

Description

To achieve automated detection of cup rupture results in strip steel welds while fulfilling requirements for high efficiency, real-time detection, standardization, and consistency of results, this study proposes a lightweight object detection algorithm based on an improved YOLOv10 framework.

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Institutions

  • Harbin University of Science and Technology

Categories

Deep Learning

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