Chinese Journal of Liquid Crystals and Displays, Volume. 40, Issue 7, 1023(2025)
Particle image velocimetry method based on ConvLSTM and LiteFlowNet architecture
Fig. 6. Examples of particle image pairs at different time instants
Fig. 7. Estimated velocity fields and streamlines for different models
Fig. 8. Estimated velocity fields and vorticity maps for different models
Fig. 9. Comparison of root mean square error(RMSE)results for different models
Fig. 10. RMSE error curves of different methods during the training process
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Xin'ai LIU, Juan MENG, Hai DU, Zhiyuan LI. Particle image velocimetry method based on ConvLSTM and LiteFlowNet architecture[J]. Chinese Journal of Liquid Crystals and Displays, 2025, 40(7): 1023
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Received: Mar. 6, 2025
Accepted: --
Published Online: Aug. 11, 2025
The Author Email: Juan MENG (mengjuan@dlou.edu.cn)