Nature

Semiconductor Wafer Defect Pattern Recognition and Classification

Semiconductor wafer defect pattern recognition and classification is a crucial area of research that underpins yield enhancement and quality assurance in microelectronics manufacturing. The discipline ...
Semiconductor Engineering

Using Automatic Defect Classification To Reduce The Escape Rate Of Defects

Automated optical inspection (AOI) is a cornerstone in semiconductor manufacturing, assembly and testing facilities, and as such, it plays a crucial role in yield management and process control.
EDN

Electroglas Intros Automated Defect Classification

Process management tools company Electroglas Inc. today introduced DefectID, its automatic defect classification software. Aimed at improving manufacturing productivity and yields for wafer ...
Semiconductor Engineering

Using Deep Learning ADC For Defect Classification For Automatic Defect Inspection

In traditional semiconductor packaging, manual defect review after automated optical inspection (AOI) is an arduous task for operators and engineers, involving review of both good and bad die. It is ...
pv magazine International

Ensemble deep learning for PV cell defect detection

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 ...
InfoQ

Reducing Verification Lead Time by 50% by Lowering Defect Slippage and Applying AI/ML Techniques

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...