The small and complicated features of TSVs give rise to different defect types. Defects can form during any of the TSV ...

Edge AI addresses high-performance, low-latency requirements by embedding intelligence directly into industrial devices.

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/ ├── ...

The European Space Agency (ESA) is accelerating a quiet revolution on the factory floor: using artificial intelligence to design, inspect, ...

Researchers report a machine learning approach to predict LPBF defects from up-skin and down-skin angles, suggesting there might be angle-aware process control for metal AM. Laser Powder Bed Fusion ...

Abstract: As electrical devices take on more life-critical roles, such as in autonomous driving, ensuring the quality of solder joints during production becomes increasingly important. Recently, there ...

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine learning algorithm designed to identify physical anomalies in solar ...

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for millions of deaths each year according to the World Health Organization (WHO). Early detection of these diseases ...

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 ...