Raising the bar for manufacturing: Inside six smart S’pore factories earning global recognition

Explore how six smart Singapore factories are using advanced technologies to gain global recognition in manufacturing. Read ...
Scientific Research Publishing

Design of an Intelligent Campus Surveillance System, Based on Cognitive Security and the Internet of Things, for the Detection of Suspicious Activities ()

1 Department of Bachelor’s Degrees, Faculty of Applied Sciences, Denis Sassou Nguesso University, Brazzaville, Republic of the Congo. 2 Faculty of Science, Laboratory of Mathematics and Computer ...
Forbes

Machine Learning Trends For 2026

You're probably a little tired of reading or hearing about AI, right? Well, if that's the case, then you're in the right place because here, we're going to talk about machine learning (ML). Yes, it's ...
IEEE

Machine Learning Approach for Mixed type Wafer Defect Pattern Recognition by ResNet Architecture

Abstract: Semiconductor manufacturing process involves various steps: fabrication of Wafers, testing of wafers, assembly of each single die and package level final test. Out of which, testing of wafer ...
IEEE

Automated PCB Defect Identification System using Machine Learning Techniques

Abstract: Printed Circuit Boards are mostly seen in all electronic products in daily life. PCBs are easily rejected due to different kinds of defects that slow down the manufacturing process. Defects ...
EurekAlert!

Real-time, machine learning-enhanced position recognition for sub-half-wavelength precision laser nanofabrication

(a) Schematic of the laser nanofabrication system. (b) Simulated and experimentally captured images. N-defocus indicates the focal point below the sample surface, In-focus indicates the sample at the ...
pv magazine International

US researchers use machine learning to detect hidden solar array defects

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 ...
pv-magazine-usa

Machine learning models identify hidden physical defects in solar arrays

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 ...