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 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 ...

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 ...

Detecting macro-defects early in the wafer processing flow is vital for yield and process improvement, and it is driving innovations in both inspection techniques and wafer test map analysis. At 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 ...

Longitudinal (top) and axial (middle) images of X-Ray CT data of parts with 6 internal defects: a spherical clog, a stellated shaped clog, a cone shaped void, a blob shaped void, an elliptical warp of ...

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 ...