The automatic detection of surface-level irregularities—defects or anomalies—in 3D data is of significant interest for various real-world purposes, such as industrial quality inspection, ...

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.

Existing defect detection tools using ultrasound rely on phased array ultrasound. In this method, many transducers are pointed in the same direction to generate an image of that specific area. This ...

The field of additive manufacturing is undergoing a profound transformation as artificial intelligence (AI) and machine learning (ML) become integral to the ...

Abstract: Concurrency defects such as race conditions, deadlocks, and improper synchronization remain a critical challenge in developing reliable OpenMP-based parallel applications. Traditional static ...

The European Space Agency (ESA) is accelerating a quiet revolution on the factory floor: using artificial intelligence to design, inspect, ...

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 ...