Table 3 The MAE (\(\times 10^{-4}\text {s}^{-1}\)) of the four models in the test set on \(Dataset_{5000}\)
From: Deep learning method for super-resolution reconstruction of the spatio-temporal flow field
Frame number | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
|---|---|---|---|---|---|---|---|---|---|---|
MST-UNet | 3.53 | 2.49 | 2.34 | 2.31 | 2.31 | 2.29 | 2.28 | 2.27 | 2.29 | 2.32 |
SLR-UNet | 4.03 | 4.41 | 5.53 | 7.16 | 3.82 | 3.06 | 2.98 | 2.97 | 2.97 | 3.04 |
MTLR1-UNet | 3.02 | 2.94 | 2.97 | 2.99 | 3.00 | 2.99 | 2.98 | 2.98 | 2.98 | 3.02 |
MTLR2-UNet | 3.61 | 3.58 | 3.45 | 3.46 | 3.48 | 3.49 | 3.49 | 3.50 | 3.53 | 3.61 |