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 ...

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 ...

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: The structural integrity of metallic bullet casings is critical not only for military applications—where a single defective casing can compromise ammunition performance and jeopardize ...

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 ...

Chip scale package (CSP) light-emitting diode (LED) is miniaturized light-emitting diodes designed for automated chip-level packaging. Defect detection is particularly challenging due to the high ...

To address the issues of missed detection and false detection during the defect inspection process of the PCB, an improved YOLOv7-based algorithm for PCB defect detection is proposed. Firstly, the ...

TDK SensEI’s edgeRX Vision system, powered by advanced AI, accurately detects defects in components as small as 1.0×0.5 mm in real time. Operating at speeds up to 2000 parts per minute, it reduces ...

Division of Applied Chemistry, Faculty of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan ...