The dataset is already organized in YOLO format in the steel_dataset/ directory. If you need to reorganize from original format, see utility/reorganize_dataset.py. steel-defect-detection/ ├── ...

Introduction: Accurate defect detection in dissimilar metal welds (DMWs) remains a major challenge due to heterogeneous microstructures and imaging noise. Methods: In this study, we propose a novel ...

External defect detection is a crucial step in Orah mandarin citrus grading. However, in existing defect detection algorithms by image processing, Orah mandarin surfaces exhibit characteristics such ...

To address the issues of missed detection and false detection during the defect inspection process of the PCB, an improved YOLOv7-based algorithm for PCB defect detection is proposed. Firstly, the ...

Defect detection requirements on the order of 10 defective parts per million (DPPM) are driving improvements in inspection tools’ resolution and throughput at foundries and OSATs. However, defects ...

Scientists from the federally funded Argonne National Laboratory in Illinois and the University of Virginia have developed a new approach for detecting defects in metal parts produced by 3D printing.

Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...

Abstract: In the area of manufacturing, ensuring the integrity of structural elements of steel parts is important for safety and quality control The traditional ...