| Ship detection in SAR images via local contrast of Fisher vectors X Wang, G Li, XP Zhang, Y He IEEE Transactions on geoscience and remote sensing 58 (9), 6467-6479, 2020 | 44 | 2020 |
| Two-level block matching pursuit for polarimetric through-wall radar imaging X Wang, G Li, Y Liu, MG Amin IEEE Transactions on Geoscience and Remote Sensing 56 (3), 1533-1545, 2017 | 38 | 2017 |
| Detection of Sparse Stochastic Signals with Quantized Measurements in Sensor Networks X Wang, G Li, P Varshney IEEE Transactions on Signal Processing 67 (8), 2210-2220, 2019 | 33 | 2019 |
| A fast CFAR algorithm based on density-censoring operation for ship detection in SAR images X Wang, G Li, XP Zhang, Y He IEEE Signal Processing Letters 28, 1085-1089, 2021 | 32 | 2021 |
| Detection of sparse signals in sensor networks via locally most powerful tests X Wang, G Li, PK Varshney IEEE Signal Processing Letters 25 (9), 1418-1422, 2018 | 31 | 2018 |
| Distributed detection of sparse stochastic signals with quantized measurements: The generalized Gaussian case X Wang, G Li, C Quan, PK Varshney IEEE Transactions on Signal Processing 67 (18), 4886-4898, 2019 | 29 | 2019 |
| Distributed Detection of Weak Signals From One-Bit Measurements Under Observation Model Uncertainties X Wang, G Li, P Varshney IEEE Signal Processing Letter 29 (3), 415-419, 2019 | 23 | 2019 |
| Enhanced 1-Bit Radar Imaging by Exploiting Two-Level Block Sparsity X Wang, G Li, Y Liu, MG Amin IEEE Transactions on Geoscience and Remote Sensing 57 (2), 1131-1141, 2019 | 23 | 2019 |
| Distributed detection of sparse stochastic signals via fusion of 1-bit local likelihood ratios C Li, Y He, X Wang, G Li, PK Varshney IEEE Signal Processing Letters 26 (12), 1738-1742, 2019 | 22 | 2019 |
| Look-ahead hybrid matching pursuit for multipolarization through-wall radar imaging X Wang, G Li, Q Wan, RJ Burkholder IEEE Transactions on Geoscience and Remote Sensing 55 (7), 4072-4081, 2017 | 21 | 2017 |
| Ship detection in SAR images via enhanced nonnegative sparse locality-representation of Fisher vectors X Wang, G Li, A Plaza, Y He IEEE Transactions on Geoscience and Remote Sensing 59 (11), 9424-9438, 2021 | 19 | 2021 |
| Proposal-Copula-Based Fusion of Spaceborne and Airborne SAR Images for Ship Target Detection⁎⁎ X Wang, D Zhu, G Li, XP Zhang, Y He Information Fusion 77, 247-260, 2022 | 14 | 2022 |
| ConvTransNet: A CNN-transformer network for change detection with multi-scale global-local representations W Li, L Xue, X Wang, G Li IEEE Transactions on Geoscience and Remote Sensing, 2023 | 12 | 2023 |
| Frequency-adaptive learning for SAR ship detection in clutter scenes L Zhang, Y Liu, W Zhao, X Wang, G Li, Y He IEEE Transactions on Geoscience and Remote Sensing, 2023 | 12 | 2023 |
| Revisiting SLIC: Fast superpixel segmentation of marine SAR images using density features X Wang, G Li, A Plaza, Y He IEEE Transactions on Geoscience and Remote Sensing 60, 1-18, 2022 | 12 | 2022 |
| Ship detection in SAR images by aggregating densities of Fisher vectors: Extension to a global perspective X Wang, G Li, A Plaza, Y He IEEE Transactions on Geoscience and Remote Sensing 60, 1-13, 2021 | 12 | 2021 |
| Adaptive superpixel segmentation of marine SAR images by aggregating Fisher vectors X Wang, Y He, G Li, A Plaza IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2021 | 12 | 2021 |
| An improved attention-guided network for arbitrary-oriented ship detection in optical remote sensing images C Qin, X Wang, G Li, Y He IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2022 | 8 | 2022 |
| Mctnet: a multi-scale cnn-transformer network for change detection in optical remote sensing images W Li, L Xue, X Wang, G Li 2023 26th International Conference on Information Fusion (FUSION), 1-5, 2023 | 7 | 2023 |
| Adaptive superpixel segmentation with Fisher vectors for ship detection in SAR images X Wang, G Li, A Plaza IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 7 | 2020 |
Gang LiProfessor, Department of Electronic Engineering, Tsinghua UniversityVerified email at tsinghua.edu.cn
