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.

Machine learning (ML) is reshaping pipeline integrity management (PIM) from physics-based to data-driven paradigms. This ...

BACKGROUND: Congenital heart disease (CHD), the most common birth defect and a leading cause of infant mortality, is ...

NVIDIA GTC Taipei — NVIDIA today announced that TSMC, the world’s leading semiconductor company, is using NVIDIA accelerated computing and AI to advance semiconductor design and manufacturing.

Nvidia and the world’s largest foundry TSMC are collaborating to speed up semiconductor design and manufacturing. Under the ...

NVIDIA (NASDAQ:NVDA) revealed that Taiwan Semiconductor Manufacturing Co. (NYSE:TSM) is deploying a range of its artificial ...

TSMC has expanded its three-decade partnership with NVIDIA by integrating accelerated computing, CUDA-X libraries, and machine learning models directly into its semiconductor fabrication facilities to ...

In this era of digital transformation, buzzwords like ‘Industry 4.0’ and ‘digitalization’ have become part of our daily vocabulary. But behind these trendy terms lies a potent technological innovation ...

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Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...

At present, surface defect equipment based on machine vision has widely replaced artificial visual inspection in various industrial fields, including 3C, automobiles, home appliances, machinery ...

The proposed method employs a thresholded pixel-wise difference between reconstructed image and input image to localize anomaly. The threshold is determined by first using a subset of anomalous-free ...