Comparison of super-resolution deep learning models for flow imaging-Reference-Cited by-同舟云学术

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Comparison of super-resolution deep learning models for flow imaging

Published:2024-10 Issue: Volume:283 Page:106396
ISSN:0045-7930
Container-title:Computers & Fluids
language:en
Short-container-title:Computers & Fluids

Author:

Sofos Filippos^ORCID,Drikakis Dimitris^ORCID,Kokkinakis Ioannis William^ORCID

Funder

Horizon Europe

Publisher

Elsevier BV

Reference65 articles.

1. Coherent structures and turbulent model refinement in oblique shock/hypersonic turbulent boundary layer interactions;Yu;Phys Fluids,2023

2. Can artificial intelligence accelerate fluid mechanics research?;Drikakis;Fluids,2023

3. Machine learning-based approach: global trends, research directions, and regulatory standpoints;Pugliese;Data Sci Manag,2021

4. Machine-learning methods for computational science and engineering;Frank;Computation,2020

5. Developments in image processing using deep learning and reinforcement learning;Valente;J Imag,2023

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