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 ...

Researchers from Northwestern University, University of Virginia, Carnegie Mellon University, and Argonne National Laboratory have made a significant advancement in defect detection and process ...

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

Modern advanced packaging processes and shrinking semiconductor device sizes mean that it is vital to consistently eliminate sub-20 nm defects and surface contaminants. To do this effectively, the ...

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 ...

As a seasoned tester, the responsibilities in defect management extend beyond the routine tasks of reporting issues and verifying resolutions. While these ...

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 ...