VIF-Net: Interface completion in full waveform inversion using fusion networks
Z Deng, Q Xu, F Min, Y Xiang - Computers & Geosciences, 2024 - Elsevier
Deep learning full waveform inversion (DL-FWI) distinguishes itself from traditional physics-
based methods for its robust nonlinear fitting, rapid prediction, and reduced reliance on …
based methods for its robust nonlinear fitting, rapid prediction, and reduced reliance on …
Multi-frequency Neural Born Iterative Method for Solving 2-D Inverse Scattering Problems
In this work, we propose a deep learning-based imaging method for addressing the multi-
frequency electromagnetic (EM) inverse scattering problem (ISP). By combining deep …
frequency electromagnetic (EM) inverse scattering problem (ISP). By combining deep …
AUTL: An Attention U-Net transfer learning inversion framework for magnetotelluric data
C Gao, Y Li, X Wang - IEEE Geoscience and Remote Sensing …, 2024 - ieeexplore.ieee.org
Given the limited number of labeled magnetotelluric (MT) filed data samples, current neural
network (NN) inversions for MT are primarily rely on synthetic data, which may not fully …
network (NN) inversions for MT are primarily rely on synthetic data, which may not fully …