Robotics & Machine Learning Daily News2024,Issue(Dec.16) :126-127.

Findings from Beijing Information Science and Technology University Reveals New Findings on Support Vector Machines (A Pipeline Leakage Aperture Identification Method Based On Cnn-svm Considering Sample Granularity)

Robotics & Machine Learning Daily News2024,Issue(Dec.16) :126-127.

Findings from Beijing Information Science and Technology University Reveals New Findings on Support Vector Machines (A Pipeline Leakage Aperture Identification Method Based On Cnn-svm Considering Sample Granularity)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Current study results on Machine Learn ing - Support Vector Machines have beenpublished. According to news reporting o riginating from Beijing, People’s Republic of China, by NewsRxcorrespondents, r esearch stated, “The accurate identification of pipeline leakage apertures is cr ucialfor safeguarding the environment and conserving resources. This article pr oposes a novel approach foridentifying pipeline leakage apertures through the f usion of convolutional neural network and supportvector machine (CNN-SVM).”

Key words

Beijing/People’s Republic of China/Asi a/Machine Learning/Support Vector Machines/Beijing Information Science and Te chnology University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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