Machine vision for defect detection and recognition has evolved from classical image‐processing workflows—such as thresholding, edge detection and template matching—to sophisticated deep learning ...

A new study explores deep learning for image-based defect detection during 3D printing, looking to catch bad builds.

TDK SensEI’s edgeRX Vision system, powered by advanced AI, accurately detects defects in components as small as 1.0×0.5 mm in real time. Operating at speeds up to 2000 parts per minute, it reduces ...

Detecting sub-5nm defects creates huge challenges for chipmakers, challenges that have a direct impact on yield, reliability, and profitability. In addition to being smaller and harder to detect, ...

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 ...