Research on target defect detection algorithm based on improved YOLO-V7
DOI:
https://doi.org/10.54097/hset.v56i.10589Keywords:
YOLO-V7; Target defect detection; Slou; Iron and steel surfaces; Quality control.Abstract
The goal of this study is to increase target identification accuracy and defect detection performance using the enhanced YOLO-V7 target defect detection algorithm. You Only Look Once version 7 is referred to as YOLO-V7 and is a well-liked real-time target identification technique. To make high-quality goods, however, it is essential to find flaws, and the traditional YOLO-V7 has certain restrictions when it comes to addressing specific flaws. To get around these restrictions, we implemented a number of changes to YOLO-V7. The study's enhanced YOLO-V7 target defect detection algorithm may find use in the areas of industrial automation, quality assurance, and safety monitoring.
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