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Towards physics-informed convolutional networks for optical flow estimation in particle image velocimetry using self-attention
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.ORCID iD: 0009-0005-5670-2022
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.ORCID iD: 0000-0003-1845-6199
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.ORCID iD: 0000-0003-4879-8261
2025 (English)Conference paper, Oral presentation with published abstract (Refereed)
Place, publisher, year, edition, pages
2025.
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Fluid Mechanics
Research subject
Experimental Mechanics
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URN: urn:nbn:se:ltu:diva-115095OAI: oai:DiVA.org:ltu-115095DiVA, id: diva2:2006050
Conference
21th International Symposium on Flow Visualization (ISFV21), Tokyo, Japan, June 21-25, 2025
Available from: 2025-10-13 Created: 2025-10-13 Last updated: 2025-10-21Bibliographically approved

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Anjaneya Reddy, YuvarajendraWahl, JoelSjödahl, Mikael

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