Few ideas in modern manufacturing are as deceptively simple, and as stubbornly difficult, as teaching a machine to recognize when something looks wrong. A production line may turn out thousands of ...
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 single undetected mispick in a weaving line, a hairline scratch on rolled steel, or a subtle stain on finished fabric can ...
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 ...
A study published in Molecules and led by researchers from the Changchun Institute of Optics, Fine Mechanics and Physics (CIOMP) of the Chinese Academy of Sciences demonstrated how deep learning can ...
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.
Vision inspection systems for glass defect detection are industrial vision inspection systems designed to automatically detect minute scratches, foreign objects, bubbles, cracks, surface ...
Chipmakers worldwide consider Automatic Test Pattern Generation (ATPG) their go-to method for achieving high test coverage in production. ATPG generates test patterns designed to detect faults in the ...
US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...
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 ...
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