In software testing, keeping the user interface consistent and error-free requires regular checks after every update. Teams ...
Researchers have published research detailing their development of an AI framework to detect defects in additively ...
Smart manufacturing technologies, such as digital tools and connected systems, can improve visibility, performance and ...
Artificial intelligence is reshaping additive manufacturing by enabling real-time process optimization, automated design generation, and advanced quality control. From aerospace to food production, AI ...
Ford engineers are studying whether AI can play a role in detecting faulty run-downs. To do that, they first had to determine ...
Abstract: Fabric defect detection plays a pivotal role in the textile industry, as it ensures product quality and minimizes waste. Traditional machine learning models often struggle with the scarcity ...
Effectively detecting subtle surface defects in strip steel is vital for industrial quality assurance; however, most existing approaches fail to strike an optimal balance between accuracy 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 ...
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 ...
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