The historic first image of the Messier 87 (M87) supermassive black hole, captured using the Event Horizon Telescope, has ...
Abstract: Insulator defect detection (IDD) of transmission lines is crucial for power system safety and stability, with Un-manned Aerial Vehicle (UAV)-based machine learning methods becoming prevalent ...
The key idea behind our framework is that life produces molecules with purpose, while nonliving chemistry does not. Cells ...
The software tool uses self-supervised learning to detect long-term defects in solar assets weeks or years before ...
A booth demo highlights why the Cognex In-Sight 3800 makes quick work of executing inspection tasks on high-speed ...
US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...
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 ...
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 ...
ABSTRACT: Regular pipeline inspections are crucial for timely identification of critical defects and ensuring pipeline integrity. To address the challenges of detecting defects in PE gas pipelines ...