Leakage-safe machine learning for hydrogen embrittlement detection in 316L stainless steel using a region-held-out evaluation of texture and deep features in SEM micrographs
Read the original at arxiv.org→arXiv:2609.28567v1 Announce Type: new Abstract: Scanning electron microscopy (SEM) is routinely used to characterize the microstructural changes caused by hydrogen embrittlement (HE) in structural steels. Machine...
Original headline: "Leakage-Safe Machine Learning for Hydrogen Embrittlement Detection in 316L Stainless Steel: A Region-Held-Out Evaluation of Texture and Deep Features in SEM Micrographs"
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- Sep 26, 04:00 UTC arXiv cs.LG lead source Leakage-Safe Machine Learning for Hydrogen Embrittlement Detection in 316L Stainless Steel: A Region-Held-Out Evaluation of Texture and Deep Features in SEM Micrographs