| The linear random forest algorithm and its advantages in machine learning assisted logging regression modeling Y Ao, H Li, L Zhu, S Ali, Z Yang Journal of Petroleum Science and Engineering 174, 776-789, 2019 | 288 | 2019 |
| Intelligent logging lithological interpretation with convolution neural networks L Zhu, H Li, Z Yang, C Li, Y Ao Petrophysics 59 (06), 799-810, 2018 | 78 | 2018 |
| Identifying channel sand-body from multiple seismic attributes with an improved random forest algorithm Y Ao, H Li, L Zhu, S Ali, Z Yang Journal of Petroleum Science and Engineering 173, 781-792, 2019 | 58 | 2019 |
| Logging lithology discrimination in the prototype similarity space with random forest Y Ao, H Li, L Zhu, S Ali, Z Yang IEEE Geoscience and Remote Sensing Letters 16 (5), 687-691, 2018 | 46 | 2018 |
| Multitask learning for super-resolution of seismic velocity model Y Li, J Song, W Lu, P Monkam, Y Ao IEEE Transactions on Geoscience and Remote Sensing 59 (9), 8022-8033, 2020 | 42 | 2020 |
| Probabilistic logging lithology characterization with random forest probability estimation Y Ao, L Zhu, S Guo, Z Yang Computers & Geosciences 144, 104556, 2020 | 42 | 2020 |
| Seismic dip estimation with a domain knowledge constrained transfer learning approach Y Ao, W Lu, P Xu, B Jiang IEEE Transactions on Geoscience and Remote Sensing 60, 1-16, 2021 | 33 | 2021 |
| Choosing classification algorithms and its optimum parameters based on data set characteristics Y Zhongguo, L Hongqi, S Ali, A Yile Journal of Computers 28 (5), 26-38, 2017 | 32 | 2017 |
| Seismic structural curvature volume extraction with convolutional neural networks Y Ao, W Lu, B Jiang, P Monkam IEEE Transactions on Geoscience and Remote Sensing 59 (9), 7370-7384, 2020 | 31 | 2020 |
| Super-resolution of seismic velocity model guided by seismic data Y Li, J Song, W Lu, P Monkam, Y Ao IEEE Transactions on Geoscience and Remote Sensing 60, 1-12, 2021 | 24 | 2021 |
| Seismic inversion based on 2D-CNNs and domain adaption Q Wang, Y Wang, Y Ao, W Lu IEEE Transactions on Geoscience and Remote Sensing 60, 1-12, 2022 | 20 | 2022 |
| UB-Net: Improved seismic inversion based on uncertainty backpropagation Q Ma, Y Wang, Y Ao, Q Wang, W Lu IEEE Transactions on Geoscience and Remote Sensing 60, 1-11, 2022 | 20 | 2022 |
| Combining regression kriging with machine learning mapping for spatial variable estimation X Li, Y Ao, S Guo, L Zhu IEEE Geoscience and Remote Sensing Letters 17 (1), 27-31, 2019 | 9 | 2019 |
| Seismic stratigraphic interpretation based on deep active learning X Gu, W Lu, Y Ao, Y Li, C Song IEEE Transactions on Geoscience and Remote Sensing 61, 1-11, 2023 | 8 | 2023 |
| Sequence-to-sequence borehole formation property prediction via multi-task deep networks with sparse core calibration Y Ao, W Lu, Q Hou, B Jiang Journal of Petroleum Science and Engineering 208, 109637, 2022 | 6 | 2022 |
| A SCiForest based semi-supervised learning method for the seismic interpretation of channel sand-body Y Ao, H Li, L Zhu, Z Yang Journal of Applied Geophysics 167, 51-62, 2019 | 6 | 2019 |
| Synthesize nuclear magnetic resonance T2 spectrum from conventional logging responses with spectrum regression forest Y Ao, W Lu, Q Hou, B Jiang IEEE Geoscience and Remote Sensing Letters 18 (10), 1726-1730, 2020 | 5 | 2020 |
| Seismic inversion based on 2D-CNN and multi-task learning Q Wang, Y Wang, Y Ao, W Lu 82nd EAGE annual conference & exhibition 2021 (1), 1-5, 2021 | 4 | 2021 |
| An alternative approach for machine learning seismic interpretation and its application in Daqing Oilfield Y Ao, H Li, Z Yang, L Zhu SEG International Exposition and Annual Meeting, SEG-2018-2989898, 2018 | 3 | 2018 |
| Lane detection by combining trajectory clustering and curve complexity computing in urban environments Z Yang, H Li, S Ali, Y Ao, S Guo 2017 13th International Conference on Semantics, Knowledge and Grids (SKG …, 2017 | 3 | 2017 |
Patrice MonkamAssistant Professor, Medicine and Biological Information Engineering, Northeastern Universitymails.tsinghua.edu.cn üzerinde doğrulanmış e-posta adresine sahip