learning

3D U-Net based joint imaging
Efficient deep learning framework for field applications
3D U-Net based joint imaging
Deep perceptual losses for joint imaging
Enforcing structural similarity using deep perceptual losses extracted from the pretrained network
Deep perceptual losses for joint imaging
Robust progressive learning For GPR full waveform inversion
Self-regularized training scheme and use augmented training dataset to improve the stability of the DNN model
Robust progressive learning For GPR full waveform inversion
Deep learning enhanced joint imaging
Model-to-model deep learning joint imaging framework using U-Net
Deep learning enhanced joint imaging
RNN-based wave propagation simulation
Equivalent implementation of recurrent neural network (RNN) for simulating wave propagation using FDTD
RNN-based wave propagation simulation
Physics-driven deep-learning inverse solver for subsurface imaging
Incorporating the forward modeling as the regularization to train the network
Physics-driven deep-learning inverse solver for subsurface imaging
PINN for EM simulations
A Maxwell’s equations based deep learning method for time domain electromagnetic simulations
PINN for EM simulations