How deep learning enhances rule-based machine vision in quality and process control inspection applications. How edge learning compares to deep learning in machine-vision applications. Which ...

Researchers have developed a new method for detecting defects in additively manufactured components. Researchers at the University of Illinois Urbana-Champaign have developed a new method for ...

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 ...

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 ...

AI plays a role in improving defect capture rate and distinguishing between yield-killing and nuisance defects. New developments in wafer edge inspection are proving essential to bonded wafer yields.

Semiconductor inspection has always been a scalability problem. Inspection teams are buried in manual reviews because the machines on the line throw false rejects, miss real defects, and can’t learn ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Longitudinal (top) and axial (middle) images of X-Ray CT data of parts with 6 internal defects: a spherical clog, a stellated shaped clog, a cone shaped void, a blob shaped void, an elliptical warp of ...