In industry, the detection of anomalies such as scratches, dents, and discolorations is crucial to ensure product quality and safety. However, conventional methods rely on heavy computational ...

Researchers have developed a new method for detecting defects in additively manufactured components. Researchers at the University of Illinois Urbana-Champaign have developed a new method for ...

Researchers have tested eight stand-alone deep learning methods for PV cell fault detection and have found that their accuracy was as high as 73%. All methods were trained and tested on the ELPV ...

The system, developed by Panevo, a Canadian clear technology and manufacturing analytics company, reportedly achieved approximately 97% detection reliability with minimal false positives of Muskoka’s ...

A new technical paper titled “Towards Improved Semiconductor Defect Inspection for high-NA EUVL based on SEMI-SuperYOLO-NAS” was published by researchers at KU Leuven, imec, Ghent University, and ...

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

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 ...

Researchers have designed a robust image-based anomaly detection (AD) framework with illumination enhancement and noise suppression features that can enhance the detection of subtle defects in ...