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Mining Multimodal Fatigue Data Using Reasoning Foundation Models and Formalized Domain Knowledge

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Published in:Integrating Materials and Manufacturing Innovation
Format: Online Article RSS Article
Published: 2026
Subjects:
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container_title Integrating Materials and Manufacturing Innovation
description
discipline_display Manufacturing and Technology
discipline_facet Manufacturing and Technology
format Online Article
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genre Journal Article
id rss_article:63435
institution FRELIP
journal_source_facet Integrating Materials and Manufacturing Innovation
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Mining Multimodal Fatigue Data Using Reasoning Foundation Models and Formalized Domain Knowledge
Manufacturing and Technology
General
Manufacturing and Technology
sub_discipline_display General
sub_discipline_facet General
subject_display Manufacturing and Technology
General
Manufacturing and Technology
Manufacturing and Technology
General
Manufacturing and Technology
subject_facet Manufacturing and Technology
General
Manufacturing and Technology
title Mining Multimodal Fatigue Data Using Reasoning Foundation Models and Formalized Domain Knowledge
title_auth Mining Multimodal Fatigue Data Using Reasoning Foundation Models and Formalized Domain Knowledge
title_full Mining Multimodal Fatigue Data Using Reasoning Foundation Models and Formalized Domain Knowledge
title_fullStr Mining Multimodal Fatigue Data Using Reasoning Foundation Models and Formalized Domain Knowledge
title_full_unstemmed Mining Multimodal Fatigue Data Using Reasoning Foundation Models and Formalized Domain Knowledge
title_short Mining Multimodal Fatigue Data Using Reasoning Foundation Models and Formalized Domain Knowledge
title_sort mining multimodal fatigue data using reasoning foundation models and formalized domain knowledge
topic Manufacturing and Technology
General
Manufacturing and Technology
url https://link.springer.com/article/10.1007/s40192-026-00442-9