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 ...
Nature

Semiconductor Wafer Defect Pattern Recognition and Classification

Semiconductor wafer defect pattern recognition and classification is a crucial area of research that underpins yield enhancement and quality assurance in microelectronics manufacturing. The discipline ...
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.
Science Daily

Researchers use machine learning to detect defects in additive manufacturing

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 ...
Semiconductor Engineering

Domain Adaptation for Image Classification of Defects in Semiconductor Manufacturing (Infineon, U. Padova et al.)

A new technical paper titled “Domain Adaptation for Image Classification of Defects in Semiconductor Manufacturing” was published by researchers at Infineon Technologies, University of Padova and ...
EurekAlert!

Researchers use machine learning to detect defects in additive manufacturing

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 ...