The paper 🔺Xintao Chai et al., 2020, Deep learning for irregularly and regularly missing data reconstruction🔺 uses mixed synthetic and field datasets to train U-net like the neural network to combat the problem of missing data.
Once the network is fully trained, they test it on a diverse field data set and compare it with the Fourier transform interpolation method. The testing shows the effectiveness, superiority, and generalization capability of the proposed technique.
Link to the LinkedIn post