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 review the recent advances of deep learning-basedimage anomaly detection since the rapid development ofdeep learning can bring the capabilities of image anomaly detection into the factory ...
A research project undertaken by the Bristol Composites Institute (BCI) at the University of Bristol used laser profile sensors from Micro-Epsilon to detect defects formed during the composites ...
Advanced machine learning is beginning to make inroads into yield enhancement methodology as fabs and equipment makers seek to identify defectivity patterns in wafer images with greater accuracy and ...
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 ...
The PV industry has been playing a game of ‘whack a mole’ in tackling module defects over the past decade. Image: Kiwa PI Berlin. Solar modules manufactured in countries such as the United States, ...
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