Vortex-U-Net: An efficient and effective vortex detection approach based on U-Net structure-Reference-Cited by-同舟云学术

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Vortex-U-Net: An efficient and effective vortex detection approach based on U-Net structure

Published:2022-01 Issue: Volume:115 Page:108229
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Deng Liang,Bao Wenchun,Wang Yueqing,Yang Zhigong,Zhao Dan,Wang Fang,Bi Chongke,Guo Yang

Publisher

Elsevier BV

Subject

Software

Reference45 articles.

1. Detection and visualization of vortices;Jiang,2005

2. Review of vortex identification methods;Epps,2017

3. The state of the art in vortex extraction;Günther;Comput. Graph. Forum,2018

4. Analysis and Visualization of Vortices: Topological, Physics-Based and Deep Learning Techniques;Marzieh,2019

5. Selective visualization of vortices in hydrodynamic flows;Sadarjoen,2002

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1. Novel deep learning methods for 3D flow field segmentation and classification;Expert Systems with Applications;2024-10

2. FFEINR: flow feature-enhanced implicit neural representation for spatiotemporal super-resolution;Journal of Visualization;2024-02-19

3. Identification of vortex in unstructured mesh with graph neural networks;Computers & Fluids;2024-01

4. U-net based vortex detection in Bose–Einstein condensates with automatic correction for manually mislabeled data;Scientific Reports;2023-12-02

5. Flow Field Feature Extraction and Tracking Based on Spatial Similarity Metrics;2023 Nicograph International (NicoInt);2023-06

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