Magnetization vector imaging for borehole magnetic data based on magnitude magnetic anomaly S Liu, X Hu, T Liu, J Feng, W Gao, L Qiu Geophysics 78 (6), D429-D444, 2013 | 95 | 2013 |
3D magnetization vector inversion of magnetic data: Improving and comparing methods S Liu, X Hu, H Zhang, M Geng, B Zuo Pure and Applied Geophysics 174, 4421-4444, 2017 | 70 | 2017 |
2D sequential inversion of total magnitude and total magnetic anomaly data affected by remanent magnetization S Liu, X Hu, Y Xi, T Liu, S Xu Geophysics 80 (3), K1-K12, 2015 | 65 | 2015 |
Recovering 3D basement relief using gravity data through convolutional neural networks S He, H Cai, S Liu, J Xie, X Hu Journal of Geophysical Research: Solid Earth 126 (10), e2021JB022611, 2021 | 59 | 2021 |
Deep learning 3D sparse inversion of gravity data R Huang, S Liu, R Qi, Y Zhang Journal of Geophysical Research: Solid Earth 126 (11), e2021JB022476, 2021 | 58 | 2021 |
3-D gravity inversion based on deep convolution neural networks Q Yang, X Hu, S Liu, Q Jie, H Wang, Q Chen IEEE geoscience and remote sensing letters 19, 1-5, 2021 | 55 | 2021 |
Particle swarm optimization inversion of magnetic data: Field examples from iron ore deposits in China S Liu, M Liang, X Hu Geophysics 83 (4), J43-J59, 2018 | 54 | 2018 |
Application of machine learning for lithofacies prediction and cluster analysis approach to identify rock type M Hussain, S Liu, U Ashraf, M Ali, W Hussain, N Ali, A Anees Energies 15 (12), 4501, 2022 | 50 | 2022 |
Inversion of magnetic data using deep neural networks Z Hu, S Liu, X Hu, L Fu, J Qu, H Wang, Q Chen Physics of the Earth and Planetary Interiors 311, 106653, 2021 | 48 | 2021 |
Fractal analysis of the effect of particle aggregation distribution on thermal conductivity of nanofluids W Wei, J Cai, X Hu, Q Han, S Liu, Y Zhou Physics Letters A 380 (37), 2953-2956, 2016 | 48 | 2016 |
A stochastic inversion method for potential field data: ant colony optimization S Liu, X Hu, T Liu Pure and Applied Geophysics 171, 1531-1555, 2014 | 42 | 2014 |
An Efficient Alternating Algorithm for the Lp-Norm Cross-Gradient Joint Inversion of Gravity and Magnetic Data Using the 2-D Fast Fourier Transform S Vatankhah, S Liu, RA Renaut, X Hu, JD Hogue, M Gharloghi IEEE Transactions on Geoscience and Remote Sensing 60, 1-16, 2022 | 41 | 2022 |
Multiple transisthmian divergences, extensive cryptic diversity, occasional long‐distance dispersal, and biogeographic patterns in a marine coastal isopod with an amphi … LA Hurtado, M Mateos, G Mattos, S Liu, PA Haye, PC Paiva Ecology and Evolution 6 (21), 7794-7808, 2016 | 38 | 2016 |
Three-dimensional inversion of magnetic data in the simultaneous presence of significant remanent magnetization and self-demagnetization: example from Daye iron-ore deposit … S Liu, M Fedi, X Hu, Y Ou, J Baniamerian, B Zuo, Y Liu, R Zhu Geophysical Journal International 215 (1), 614–634, 2018 | 37 | 2018 |
Multi-scale analysis to the gravity field of the northeastern Tibetan plateau and its geodynamic implications JC B Bi, X Hu, L Li, H Zhang, S Liu Chinese Journal of Geophysics (In Chinese) 59 (2), 543-555, 2016 | 35* | 2016 |
The formation of a geothermal anomaly and extensional structures in Guangdong, China: Evidence from gravity analyses Y Xi, G Wang, S Liu, Y Zhao, X Hu Geothermics 72, 225-231, 2018 | 34 | 2018 |
Ant colony optimisation inversion of surface and borehole magnetic data under lithological constraints S Liu, X Hu, T Liu, Y Xi, J Cai, H Zhang Journal of Applied Geophysics 112, 115-128, 2015 | 34 | 2015 |
2D inverse modeling for potential fields on rugged observation surface using constrained Delaunay triangulation S Liu, X Hu, Y Xi, T Liu Computers & Geosciences 76, 18-30, 2015 | 30 | 2015 |
Extracting induced and remanent magnetizations from magnetic data modeling S Liu, M Fedi, X Hu, J Baniamerian, B Wei, D Zhang, R Zhu Journal of Geophysical Research: Solid Earth 123 (11), 9290-9309, 2018 | 27 | 2018 |
Imaging methods versus inverse methods: an option or an alternative? S Liu, J Baniamerian, M Fedi IEEE Transactions on Geoscience and Remote Sensing 58 (5), 3484-3494, 2020 | 26 | 2020 |