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Experimental dataset investigation of deep recurrent optical flow learning for particle image velocimetry: flow past a circular cylinder
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
2024 (English)In: Measurement science and technology, ISSN 0957-0233, E-ISSN 1361-6501, Vol. 35, no 8, article id 085402Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Institute of Physics (IOP), 2024. Vol. 35, no 8, article id 085402
National Category
Fluid Mechanics and Acoustics
Research subject
Experimental Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-105449DOI: 10.1088/1361-6501/ad4387ISI: 001215214500001OAI: oai:DiVA.org:ltu-105449DiVA, id: diva2:1857462
Conference
20th edition of the International Symposium on Flow Visualization (ISFV20), Delft, Netherlands, July 10-13, 2023
Note

Full text license: CC BY 4.0; 

Part of special issue: The 20th International Symposium on Flow Visualization (ISFV20);

Available from: 2024-05-13 Created: 2024-05-13 Last updated: 2024-05-14

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fulltext(4432 kB)39 downloads
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Anjaneya Reddy, YuvarajendraWahl, JoelSjödahl, Mikael

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