| Graph attention convolution for point cloud semantic segmentation L Wang, Y Huang, Y Hou, S Zhang, J Shan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 715 | 2019 |
| Stacked sparse autoencoder modeling using the synergy of airborne LiDAR and satellite optical and SAR data to map forest above-ground biomass Z Shao, L Zhang, L Wang IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017 | 104 | 2017 |
| Remote sensing image super-resolution using sparse representation and coupled sparse autoencoder Z Shao, L Wang, Z Wang, J Deng IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2019 | 101 | 2019 |
| Super-resolution for “Jilin-1” satellite video imagery via a convolutional network A Xiao, Z Wang, L Wang, Y Ren Sensors 18 (4), 1194, 2018 | 64 | 2018 |
| MSNet: Multi-scale convolutional network for point cloud classification L Wang, Y Huang, J Shan, L He Remote Sensing 10 (4), 612, 2018 | 62 | 2018 |
| Fuzzy autoencode based cloud detection for remote sensing imagery Z Shao, J Deng, L Wang, Y Fan, NS Sumari, Q Cheng Remote Sensing 9 (4), 311, 2017 | 60 | 2017 |
| Structure-aware convolution for 3D point cloud classification and segmentation L Wang, Y Liu, S Zhang, J Yan, P Tao Remote sensing 12 (4), 634, 2020 | 7 | 2020 |
| Improving details of building façades in open LiDAR data using ground images S Zhang, P Tao, L Wang, Y Hou, Z Hu Remote Sensing 11 (4), 420, 2019 | 4 | 2019 |
| Learning geometry-image representation for 3D point cloud generation L Wang, Y Huang, P Tao, Y Hou, Y Liu arXiv preprint arXiv:2011.14289, 2020 | 3 | 2020 |
