Nature

Partial discharge defect recognition method of switchgear based on cloud-edge collaborative deep learning

To address the limitations of traditional partial discharge (PD) detection methods for switchgear, which fail to meet the requirements for real-time monitoring, rapid assessment, sample fusion, 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 ...
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.
Nature

Machine learning-powered recognition of crystalline phases and orientations in epitaxial Y-doped HfO

This study presents an efficient method for automatically identifying the crystal structure and orientation of Y-doped HfO 2-based thin films using deep learning. This approach enables large-scale ...
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 ...