Robotics & Machine Learning Daily News2024,Issue(Apr.19) :76-77.

New Machine Learning Findings from Beijing University of Chemical Technology Out lined (A Machine Learning and Finite Element Simulation-based Void Inspection fo r Higher Solder Joint Reliability)

Robotics & Machine Learning Daily News2024,Issue(Apr.19) :76-77.

New Machine Learning Findings from Beijing University of Chemical Technology Out lined (A Machine Learning and Finite Element Simulation-based Void Inspection fo r Higher Solder Joint Reliability)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reporting out of Beijing, People’s Republic of China, by NewsRx editors, research stated, “We proposed a new approachfor high -quality void inspection to enhance solder joint reliability. Using a small batc h of samples, wedeveloped an automatic detection algorithm for voids in the Cu- Sn solder joint.”

Key words

Beijing/People’s Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning/Beijing University of Chemical Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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