| Object detection in 20 years: A survey Z Zou, K Chen, Z Shi, Y Guo, J Ye Proceedings of the IEEE 111 (3), 257-276, 2023 | 3215 | 2023 |
| A spatial-temporal attention-based method and a new dataset for remote sensing image change detection H Chen, Z Shi Remote Sensing 12 (10), 1662, 2020 | 1174 | 2020 |
| Remote sensing image change detection with transformers H Chen, Z Qi, Z Shi IEEE Transactions on Geoscience and Remote Sensing 60, 1-14, 2021 | 987 | 2021 |
| Localized content-based image retrieval using semi-supervised multiple instance learning D Zhang, Z Shi, Y Song, C Zhang Asian Conference on Computer Vision, 180-188, 2007 | 354 | 2007 |
| Super-resolution for remote sensing images via local–global combined network S Lei, Z Shi, Z Zou IEEE Geoscience and Remote Sensing Letters 14 (8), 1243-1247, 2017 | 306 | 2017 |
| Multilevel cloud detection in remote sensing images based on deep learning F Xie, M Shi, Z Shi, J Yin, D Zhao IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017 | 296 | 2017 |
| Ship detection in spaceborne optical image with SVD networks Z Zou, Z Shi IEEE transactions on geoscience and remote sensing 54 (10), 5832-5845, 2016 | 289 | 2016 |
| MugNet: Deep learning for hyperspectral image classification using limited samples B Pan, Z Shi, X Xu ISPRS Journal of Photogrammetry and Remote Sensing 145, 108-119, 2018 | 272 | 2018 |
| Ship detection in high-resolution optical imagery based on anomaly detector and local shape feature Z Shi, X Yu, Z Jiang, B Li IEEE Transactions on Geoscience and Remote Sensing 52 (8), 4511-4523, 2013 | 252 | 2013 |
| Random access memories: A new paradigm for target detection in high resolution aerial remote sensing images Z Zou, Z Shi IEEE Transactions on Image Processing 27 (3), 1100-1111, 2017 | 217 | 2017 |
| Can a machine generate humanlike language descriptions for a remote sensing image? Z Shi, Z Zou IEEE Transactions on Geoscience and Remote Sensing 55 (6), 3623-3634, 2017 | 196 | 2017 |
| R-VCANet: A new deep-learning-based hyperspectral image classification method B Pan, Z Shi, X Xu IEEE Journal of selected topics in applied earth observations and remote …, 2017 | 192 | 2017 |
| Single remote sensing image dehazing J Long, Z Shi, W Tang, C Zhang IEEE Geoscience and Remote Sensing Letters 11 (1), 59-63, 2013 | 162 | 2013 |
| Fully convolutional network with task partitioning for inshore ship detection in optical remote sensing images H Lin, Z Shi, Z Zou IEEE Geoscience and Remote Sensing Letters 14 (10), 1665-1669, 2017 | 160 | 2017 |
| Blind separation of superimposed moving images using image statistics K Gai, Z Shi, C Zhang IEEE transactions on pattern analysis and machine intelligence 34 (1), 19-32, 2011 | 159 | 2011 |
| Hierarchical suppression method for hyperspectral target detection Z Zou, Z Shi IEEE transactions on geoscience and remote sensing 54 (1), 330-342, 2015 | 154 | 2015 |
| Adversarial instance augmentation for building change detection in remote sensing images H Chen, W Li, Z Shi IEEE Transactions on Geoscience and Remote Sensing 60, 1-16, 2021 | 153 | 2021 |
| Sparse Unmixing of Hyperspectral Data Using Spectral A Priori Information W Tang, Z Shi, Y Wu, C Zhang IEEE Transactions on Geoscience and Remote Sensing 53 (2), 770-783, 2014 | 152 | 2014 |
| RSPrompter: Learning to prompt for remote sensing instance segmentation based on visual foundation model K Chen, C Liu, H Chen, H Zhang, W Li, Z Zou, Z Shi IEEE Transactions on Geoscience and Remote Sensing, 2024 | 149 | 2024 |
| Transformer-based multistage enhancement for remote sensing image super-resolution S Lei, Z Shi, W Mo IEEE Transactions on Geoscience and Remote Sensing 60, 1-11, 2021 | 129 | 2021 |
Changshui ZhangDept. Automation, Tsinghua University, Beijing, ChinaVerified email at mail.tsinghua.edu.cn
