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...
| 出版年: | E3S Web of Conferences |
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| 第一著者: | |
| フォーマット: | Conference paper |
| 言語: | English |
| 出版事項: |
EDP Sciences
2025
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| 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 |