Defect detection automated in diamond, other advanced semiconductors

Materials scientists at Rice University have developed a new workflow methodology for measuring microscopic defects in ...
Nature

Visual defect obfuscation based self-supervised anomaly detection

In the manufacturing industry, ensuring product quality is of paramount importance, which can be automated by machine vision systems 1,2. Machine vision systems for defective product detection can be ...
Nature

Federated multi scale vision transformer with adaptive client aggregation for industrial defect detection

Defect detection in industrial applications is essential for maintaining product quality and operational efficiency. However, traditional deep learning methods require centralized data collection, ...
Semiconductor Engineering

Hunting For Macro Defects

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 ...
Semiconductor Engineering

Refining Vision-Language Models For Lithography Defect Detection

“Semiconductor lithography inspection requires reliable detection of small pattern defects such as bridge, burr, pinch, and contamination. In this study, we propose a two-stage vision-language ...
Aerospace and Mechanical Insider on MSN

AI-driven inspection and digital thread transform aerospace quality engineering

How might aerospace quality engineers progress from defect detection to making defects obsolete entirely? The key to doing so lies in the intersection of AI-based inspection technology, predictive ...