Robotics & Machine Learning Daily News2024,Issue(Apr.4) :39-39.

Investigators at Faculty of Electrical Engineering Detail Findings in Machine Le arning (An End-to-end Machine Learning Approach With Explanation for Time Series With Varying Lengths)

Robotics & Machine Learning Daily News2024,Issue(Apr.4) :39-39.

Investigators at Faculty of Electrical Engineering Detail Findings in Machine Le arning (An End-to-end Machine Learning Approach With Explanation for Time Series With Varying Lengths)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news reportingfrom Schmalkalden, Germany, by New sRx journalists, research stated, “An accurate prediction of complexproduct qua lity parameters from process time series by an end-to-end learning approach rema ins asignificant challenge in machine learning. A special difficulty is the app lication of industrial batch processdata because many batch processes generate variable length time series.”

Key words

Schmalkalden/Germany/Europe/Cyborgs/Emerging Technologies/Machine Learning/Faculty of Electrical Engineering

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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