To track or to detect? an ensemble framework for optimal selection X Yan, X Wu, IA Kakadiaris, SK Shah Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 65 | 2012 |
A Maxwell's equations based deep learning method for time domain electromagnetic simulations P Zhang, Y Hu, Y Jin, S Deng, X Wu, J Chen IEEE Journal on Multiscale and Multiphysics Computational Techniques 6, 35-40, 2021 | 59 | 2021 |
Progressive transfer learning for low-frequency data prediction in full-waveform inversion W Hu, Y Jin, X Wu, J Chen Geophysics 86 (4), R369-R382, 2021 | 52 | 2021 |
Access Control in Internet of Things: A Survey Y Zhang, X Wu arXiv preprint arXiv:1610.01065, 2016 | 51 | 2016 |
A supervised descent learning technique for solving directional electromagnetic logging-while-drilling inverse problems Y Hu, R Guo, Y Jin, X Wu, M Li, A Abubakar, J Chen IEEE Transactions on Geoscience and Remote Sensing 58 (11), 8013-8025, 2020 | 50 | 2020 |
First-break automatic picking with deep semisupervised learning neural network KC Tsai, W Hu, X Wu, J Chen, Z Han SEG Technical Program Expanded Abstracts 2018, 2181-2185, 2018 | 45 | 2018 |
Learn low wavenumber information in FWI via deep inception based convolutional networks Y Jin, W Hu, X Wu, J Chen SEG International Exposition and Annual Meeting, SEG-2018-2997901, 2018 | 43 | 2018 |
Parallel multiple-chain DRAM MCMC for large-scale geosteering inversion and uncertainty quantification H Lu, Q Shen, J Chen, X Wu, X Fu Journal of Petroleum Science and Engineering 174, 189-200, 2019 | 39 | 2019 |
Seismic data denoising by deep-residual networks Y Jin, X Wu, J Chen, Z Han, W Hu SEG Technical Program Expanded Abstracts 2018, 4593-4597, 2018 | 37 | 2018 |
A robust first-arrival picking workflow using convolutional and recurrent neural networks P Yuan, S Wang, W Hu, X Wu, J Chen, H Van Nguyen Geophysics 85 (5), U109-U119, 2020 | 36 | 2020 |
A physics-driven deep-learning network for solving nonlinear inverse problems Y Jin, Q Shen, X Wu, J Chen, Y Huang Petrophysics 61 (01), 86-98, 2020 | 36 | 2020 |
Automatic first arrival picking via deep learning with human interactive learning KC Tsai, W Hu, X Wu, J Chen, Z Han IEEE Transactions on Geoscience and Remote Sensing 58 (2), 1380-1391, 2019 | 33 | 2019 |
Solving geosteering inverse problems by stochastic Hybrid Monte Carlo method Q Shen, X Wu, J Chen, Z Han, Y Huang Journal of Petroleum Science and Engineering 161, 9-16, 2018 | 31 | 2018 |
Embedding topic discovery in conditional random fields model for segmenting nuclei using multispectral data X Wu, M Amrikachi, SK Shah IEEE Transactions on Biomedical Engineering 59 (6), 1539-1549, 2012 | 27 | 2012 |
Physics-guided self-supervised learning for low frequency data prediction in FWI W Hu, Y Jin, X Wu, J Chen SEG Technical Program Expanded Abstracts 2020, 875-879, 2020 | 26 | 2020 |
Using a physics-driven deep neural network to solve inverse problems for LWD azimuthal resistivity measurements Y Jin, X Wu, J Chen, Y Huang SPWLA Annual Logging Symposium, D053S015R002, 2019 | 25 | 2019 |
A theory-guided deep neural network for time domain electromagnetic simulation and inversion using a differentiable programming platform Y Hu, Y Jin, X Wu, J Chen IEEE Transactions on Antennas and Propagation 70 (1), 767-772, 2021 | 24 | 2021 |
A progressive deep transfer learning approach to cycle-skipping mitigation in FWI W Hu, Y Jin, X Wu, J Chen SEG International Exposition and Annual Meeting, D033S076R007, 2019 | 24 | 2019 |
First arrival picking using U-net with Lovasz loss and nearest point picking method P Yuan, W Hu, X Wu, J Chen, H Van Nguyen SEG Technical Program Expanded Abstracts 2019, 2624-2628, 2019 | 23 | 2019 |
Detection and classification of multi-magnetic targets using mask-RCNN Z Zhou, M Zhang, J Chen, X Wu IEEE Access 8, 187202-187207, 2020 | 19 | 2020 |