These 4 critical AI vulnerabilities are being exploited faster than defenders can respond

From prompt injection to deepfake fraud, security researchers say several flaws have no known fix. Here's what to know about them.

Combining AI with optical coherence tomography shows potential for detecting lipid-rich plaques in coronary arteries

Researchers have developed a new artificial intelligence-based approach for detecting fatty deposits inside coronary arteries using optical coherence tomography (OCT) images. Because these lipid-rich ...
IEEE

Advances and Challenges in Deep Learning for Automated Welding Defect Detection: A Technical Survey

Abstract: Automated welding defect detection has emerged as a pivotal aspect of quality assurance in high-stakes industries such as aerospace, oil and gas, and construction. This paper presents a ...
GitHub

Video Object Detection in Java with OpenCV + YOLO11 — full end-to-end tutorial

OpenCV is a set of libs written in C++ and the compiled into platform-native lib format: *.dll - for Windows, or *.dylib - for Linux / Mac OS. They can be accessed from Java via Java wrapper included ...
Frontiers

Microstructural influence on learning-based defect detection in dissimilar metal welds

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 ...
IEEE

An Efficient Defect Detection Method for MLCC Based on EHL-DETR Deep Learning Model

Abstract: Multilayer ceramic capacitors (MLCCs) may present various shapes, sizes, and subtle defects during manufacturing, which can affect their performance and functionality. However, existing ...
Scientific Research Publishing

BCN-YOLO: A Deep Learning Network for PCB Defect Detection ()

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 ...
Semiconductor Engineering

Can Your ATPG Do This? Cut Defects Escaping Detection With ML

Chipmakers worldwide consider Automatic Test Pattern Generation (ATPG) their go-to method for achieving high test coverage in production. ATPG generates test patterns designed to detect faults in the ...
Interesting Engineering

Pore no more: US scientists develop real-time defect detection for 3D metal printing

Scientists from the federally funded Argonne National Laboratory in Illinois and the University of Virginia have developed a new approach for detecting defects in metal parts produced by 3D printing.