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 ...

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 ...

Introduction: Accurate defect detection in dissimilar metal welds (DMWs) remains a major challenge due to heterogeneous microstructures and imaging noise. Methods: In this study, we propose a novel ...

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 ...

YOLOv7 is an advanced deep learning algorithm for object detection, representing an improved version of the YOLO (You Only Look Once) series. Utilizing an end-to-end training approach based on deep ...

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 ...