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Fangshu Yang
Fangshu Yang
Harbin Institute of Technology, Visiting PhD of BIG (EPFL)
Dirección de correo verificada de hit.edu.cn
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Año
Deep-learning inversion: A next-generation seismic velocity model building method
F Yang, J Ma
Geophysics 84 (4), R583-R599, 2019
4392019
Velocity model building with a modified fully convolutional network
W Wang, F Yang, J Ma
SEG International Exposition and Annual Meeting, SEG-2018-2997566, 2018
822018
Robust phase unwrapping via deep image prior for quantitative phase imaging
F Yang, TA Pham, N Brandenberg, MP Lütolf, J Ma, M Unser
IEEE Transactions on Image Processing 30, 7025-7037, 2021
412021
Deep-learning projector for optical diffraction tomography
F Yang, T Pham, H Gupta, M Unser, J Ma
Optics express 28 (3), 3905-3921, 2020
302020
Automatic salt detection with machine learning
W Wang, F Yang, J Ma
80th EAGE Conference and Exhibition 2018 2018 (1), 1-5, 2018
302018
Seismic random noise attenuation via self-supervised transfer learning
H Sun, F Yang, J Ma
IEEE geoscience and remote sensing letters 19, 1-5, 2022
192022
FWIGAN: Full‐Waveform Inversion via a Physics‐Informed Generative Adversarial Network
F Yang, J Ma
Journal of Geophysical Research: Solid Earth 128 (4), e2022JB025493, 2023
17*2023
Quantitative reconstruction of defects in multi-layered bonded composites using fully convolutional network-based ultrasonic inversion
J Rao, F Yang, H Mo, S Kollmannsberger, E Rank
Journal of Sound and Vibration 542, 117418, 2023
142023
Wasserstein distance-based full-waveform inversion with a regularizer powered by learned gradient
F Yang, J Ma
IEEE Transactions on Geoscience and Remote Sensing 61, 1-13, 2023
32023
Full-waveform Inversion Using A Learned Regularization
P Sun, F Yang, H Liang, J Ma
IEEE Transactions on Geoscience and Remote Sensing, 2023
12023
14 Regularizing Neural Network for Phase Unwrapping
T Pham, F Yang, M Unser
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