首页|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)
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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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.”
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