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