A Hybrid FEM-CNN for Image-Based Severity Prediction of Corroded Offshore Pipelines

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A Hybrid FEM-CNN for Image-Based Severity Prediction of Corroded Offshore Pipelines

The combination of the Finite Element Method (FEM) with Convolutional Neural Networks (CNNs) presents a key breakthrough in the assessment of the structural integrity of offshore pipelines. The advantage of the standard FEM is in stress visualization, but it is time-consuming due to high computation...

書誌詳細
出版年:	E3S Web of Conferences
第一著者:	Fadzil N.M.; Muda M.F.; Shahid M.D.A.; Aziz N.; Mohd M.H.; Mohd Amin N.; Mohd Hashim M.H.
フォーマット:	Conference paper
言語:	English
出版事項:	EDP Sciences 2025
オンライン･アクセス:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85217660862&doi=10.1051%2fe3sconf%2f202561204003&partnerID=40&md5=ab96cc7e26088d54d3a4a08e57ae68a4

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