New compact platforms reduce cost, footprint and complexity of automated inspection for manufacturers entering Industry ...
A research team led by Dr. Jeong Min Park of the Nano Materials Research Division at the Korea Institute of Materials Science ...
The semiconductor industry is evolving with quantum imaging and AI-driven technologies, enhancing defect detection and ...
Industrial quality inspection plays a critical role in manufacturing, from ensuring the reliability of electronics and vehicles to preventing costly failures in aerospace and energy systems.
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 ...
Abstract: This work proposes the use of machine learning-based techniques for enhanced testability and performance calibration of an industrial 79-GHz power amplifier (PA) designed for an automotive ...
A research team led by the University of Sharjah in the United Arab Emirates has developed a novel machine learning approach for fault detection in bifacial PV systems. The method combines a ...
The final, formatted version of the article will be published soon. To address the challenges of missed detection and false detection of bird droppings and dust defects caused by data imbalance during ...
During the reconstruction and expansion of expressways, defects at the roadbed junction can compromise driving safety and significantly reduce the service life of the road. Based on engineering cases, ...
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