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Yufu Niu
Yufu Niu
CSIRO | University of New South Wales
Verified email at csiro.au
Title
Cited by
Cited by
Year
Digital rock segmentation for petrophysical analysis with reduced user bias using convolutional neural networks
Y Niu, P Mostaghimi, M Shabaninejad, P Swietojanski, RT Armstrong
Water Resources Research 56 (2), e2019WR026597, 2020
822020
Coal permeability: gas slippage linked to permeability rebound
Y Niu, P Mostaghimi, I Shikhov, Z Chen, RT Armstrong
Fuel 215, 844-852, 2018
522018
An innovative application of generative adversarial networks for physically accurate rock images with an unprecedented field of view
Y Niu, Y Da Wang, P Mostaghimi, P Swietojanski, RT Armstrong
Geophysical Research Letters 47 (23), e2020GL089029, 2020
492020
Coal ash content estimation using fuzzy curves and ensemble neural networks for well log analysis
I Siregar, Y Niu, P Mostaghimi, RT Armstrong
International Journal of Coal Geology 181, 11-22, 2017
292017
Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modelling
SJ Jackson, Y Niu, S Manoorkar, P Mostaghimi, RT Armstrong
Physical Review Applied 17, 054046, 2022
262022
Super-resolved segmentation of X-ray images of carbonate rocks using deep learning
NJ Alqahtani, Y Niu, YD Wang, T Chung, Z Lanetc, A Zhuravljov, ...
Transport in Porous Media 143 (2), 497-525, 2022
242022
Geometrical-based generative adversarial network to enhance digital rock image quality
Y Niu, Y Da Wang, P Mostaghimi, JE McClure, J Yin, RT Armstrong
Physical Review Applied 15 (6), 064033, 2021
202021
Paired and Unpaired Deep Learning Methods for Physically Accurate Super-Resolution Carbonate Rock Images
Y Niu, SJ Jackson, N Alqahtani, P Mostaghimi, RT Armstrong
Transport in Porous Media 144 (3), 825-847, 2022
16*2022
Particle classification of iron ore sinter green bed mixtures by 3D X-ray microcomputed tomography and machine learning
K Tang, Y Da Wang, Y Niu, TA Honeyands, D O’Dea, P Mostaghimi, ...
Powder Technology 415, 118151, 2023
92023
Effective permeability of an immiscible fluid in porous media determined from its geometric state
F Al-Zubaidi, P Mostaghimi, Y Niu, RT Armstrong, G Mohammadi, ...
Physical Review Fluids 8 (6), 064004, 2023
62023
Dynamic X-ray micotomography of microfibrous cellulose liquid foams using deep learning
SR Muin, PT Spicer, K Tang, Y Niu, M Hosseini, P Mostaghimi, ...
Chemical Engineering Science 248, 117173, 2022
42022
A Bayesian hierarchical model for the inference between metal grade with reduced variance: Case studies in porphyry Cu deposits
Y Niu, M Lindsay, P Coghill, R Scalzo, L Zhang
Geoscience Frontiers 15 (2), 101767, 2024
12024
Applications of physically accurate deep learning for processing digital rock images
Y Niu
UNSW Sydney, 2022
12022
Scaling Deep Learning for Material Imaging: A Pseudo-3d Model for Tera-Scale 3d Domain Transfer
K Tang, R Armstrong, P Mostaghimi, Y Niu, Q Meyer, C Zhao, D Finegan, ...
Available at SSRN 4808378, 2024
2024
Opportunities for Sustainability with Minerals Value Chain Integration
M Lindsay, Y Niu, R Scalzo, SV Chambi, L Zhang, P Coghill, S Occhipinti
20th Annual Meeting of the Asia Oceania Geosciences Society, 1, 2023
2023
A Bayesian Hierarchical Model for Uncertainty Quantification of The Relationship Between Cu and Fe Grade in Porphyry Copper Deposit
Y Niu, M Lindsay, P Coghill, L Zhang
26th World Mining Congress, Brisbane, Australia, 2458-2468, 2023
2023
PROPAGATING UNCERTAINTY THROUGH THE MINERALS PIPELINE: FROM REGIONAL PROSPECTIVITY TO THE (CONVEYOR) BELT
M Lindsay, Y Niu, P Coghill, SA Occhipinti
MinProXT 2022 Mineral Prospectivity and Exploration Targeting, 15, 2022
2022
Petrophysical analysis of coal samples from Gloucester Basin, New South Wales, Australia
Y Niu
The University of New South Wales, 2018
2018
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Articles 1–18