AI model accelerates defect-based material design

Across the physical world, many intricate structures form via symmetry breaking. When a system with inherent symmetry ...

Chungnam National University Develops AI Model to Accelerate Defect-Based Material Design

Researchers at Chungnam National University have developed a deep learning method that predicts stable defect configurations in nematic liquid crystals in milliseconds rather than hours. This rapid ...
Nature

Automated Defect Detection in Sewer Pipelines Using Deep Learning

Advances in deep learning have transformed the field of infrastructure maintenance, particularly in the automated detection and characterisation of defects in sewer pipelines. Leveraging large volumes ...
Semiconductor Engineering

Using Automatic Defect Classification To Reduce The Escape Rate Of Defects

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.
Semiconductor Engineering

Classification and Localization of Semiconductor Defect Classes in Aggressive Pitches (imec, Screen)

A new technical paper titled “An Evaluation of Continual Learning for Advanced Node Semiconductor Defect Inspection” was published by Imec and SCREEN SPE Germany. “Deep learning-based semiconductor ...