Findings from Aalto University Has Provided New Data on Support Vector Machines (Drive-by Bridge Damage Detection Using Melfrequency Cepstral Coefficients and Support Vector Machine)

Robotics & Machine Learning Daily News2024，Issue(Nov.1) ：123-124.

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Findings from Aalto University Has Provided New Data on Support Vector Machines (Drive-by Bridge Damage Detection Using Melfrequency Cepstral Coefficients and Support Vector Machine)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Su pport Vector Machines. According to news reporting originating from Espoo, Finla nd, by NewsRx correspondents, research stated, “Bridge damage detection using vi bration data has been confirmed as a promising approach. Compared to the traditi onal method that typically needs to install sensors or systems directly on bridg es, the drive-by bridge damage detection method has gained increasing attention worldwide since it just needs one or a few sensors instrumented on the passing v ehicle.”

Key words

Espoo/Finland/Europe/Emerging Technol ogies/Machine Learning/Support Vector Machines/Vector Machines/Aalto Univers ity

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出版年

2024

Robotics & Machine Learning Daily News

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