A new study explores deep learning for image-based defect detection during 3D printing, looking to catch bad builds.
US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years ...
A study published in Molecules and led by researchers from the Changchun Institute of Optics, Fine Mechanics and Physics (CIOMP ...
Detecting sub-5nm defects creates huge challenges for chipmakers, challenges that have a direct impact on yield, reliability, and ...
Chipmakers worldwide consider Automatic Test Pattern Generation (ATPG) their go-to method for achieving high test coverage in ...
The contemporary fast-moving high-tech environment brings a strong urgency to efficient management of defects within software in ...
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