| Deep-learning for super-resolution full-waveform lidar G Liu, J Ke Optoelectronic Imaging and Multimedia Technology VI 11187, 245-252, 2019 | 9 | 2019 |
| CNN-based Super-resolution Full-waveform LiDAR G Liu, J Ke, EY Lam Digital Holography and Three-Dimensional Imaging, JW2A. 29, 2020 | 4 | 2020 |
| Full-waveform LiDAR echo decomposition based on dense and residual neural networks G Liu, J Ke Applied Optics 61 (9), F15-F24, 2022 | 3 | 2022 |
| End-to-End Full-Waveform Echo Decomposition Based on Self-Attention Classification and U-Net Decomposition G Liu, J Ke IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2022 | 2 | 2022 |
| Dense and Residual Neural Networks for Full-waveform LiDAR Echo Decomposition G Liu, J Ke Imaging Systems and Applications, IF4D. 3, 2021 | 1 | 2021 |
| Recurrent Large Kernel Attention Network for Efficient Single Infrared Image Super-Resolution G Liu, S Zhou, X Chen, W Yue, J Ke IEEE Access, 2023 | | 2023 |
| A super-resolution imaging system based on sub-pixel camera shifting G Liu, Q Zhou II, L Zhang, J Ke Optoelectronic Imaging and Multimedia Technology V 10817, 195-203, 2018 | | 2018 |
