| From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution Y Xiao, Q Yuan, K Jiang, J He, Y Wang, L Zhang Information Fusion 96, 297-311, 2023 | 86 | 2023 |
| Machine learning in pansharpening: A benchmark, from shallow to deep networks LJ Deng, G Vivone, ME Paoletti, G Scarpa, J He, Y Zhang, J Chanussot, ... IEEE Geoscience and Remote Sensing Magazine 10 (3), 279-315, 2022 | 81 | 2022 |
| Ntire 2022 spectral recovery challenge and data set B Arad, R Timofte, R Yahel, N Morag, A Bernat, Y Cai, J Lin, Z Lin, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 78 | 2022 |
| Space-time super-resolution for satellite video: A joint framework based on multi-scale spatial-temporal transformer Y Xiao, Q Yuan, J He, Q Zhang, J Sun, X Su, J Wu, L Zhang International Journal of Applied Earth Observation and Geoinformation 108 …, 2022 | 72 | 2022 |
| Spectral response function-guided deep optimization-driven network for spectral super-resolution J He, J Li, Q Yuan, H Shen, L Zhang IEEE Transactions on Neural Networks and Learning Systems 33 (9), 4213-4227, 2022 | 66 | 2022 |
| Local-Global Temporal Difference Learning for Satellite Video Super-Resolution Y Xiao, Q Yuan, K Jiang, X Jin, J He, L Zhang, C Lin IEEE Transactions on Circuits and Systems for Video Technology, 1-14, 2023 | 42 | 2023 |
| EDiffSR: An efficient diffusion probabilistic model for remote sensing image super-resolution Y Xiao, Q Yuan, K Jiang, J He, X Jin, L Zhang IEEE Transactions on Geoscience and Remote Sensing, 2023 | 37 | 2023 |
| PoNet: A universal physical optimization-based spectral super-resolution network for arbitrary multispectral images J He, Q Yuan, J Li, L Zhang Information Fusion 80, 205-225, 2022 | 34 | 2022 |
| Spectral super-resolution meets deep learning: Achievements and challenges J He, Q Yuan, J Li, Y Xiao, D Liu, H Shen, L Zhang Information Fusion, 101812, 2023 | 25 | 2023 |
| DsTer: A dense spectral transformer for remote sensing spectral super-resolution J He, Q Yuan, J Li, Y Xiao, X Liu, Y Zou International Journal of Applied Earth Observation and Geoinformation 109 …, 2022 | 24 | 2022 |
| TTST: A Top-k Token Selective Transformer for Remote Sensing Image Super-Resolution Y Xiao, Q Yuan, K Jiang, J He, CW Lin, L Zhang IEEE Transactions on Image Processing, 2024 | 23 | 2024 |
| Generating a long-term (2003− 2020) hourly 0.25° global PM2. 5 dataset via spatiotemporal downscaling of CAMS with deep learning (DeepCAMS) Y Xiao, Y Wang, Q Yuan, J He, L Zhang Science of The Total Environment 848, 157747, 2022 | 18 | 2022 |
| An efficient unfolding network with disentangled spatial-spectral representation for hyperspectral image super-resolution D Liu, J Li, Q Yuan, L Zheng, J He, S Zhao, Y Xiao Information Fusion 94, 92-111, 2023 | 17 | 2023 |
| 数据驱动的多源遥感信息融合研究进展 张良培， 何江， 杨倩倩， 肖屹， 袁强强 测绘学报 51 (7), 1317-1337, 2022 | 11* | 2022 |
| SPIRIT: Spectral Awareness Interaction Network with Dynamic Template for Hyperspectral Object Tracking Y Chen, Q Yuan, Y Tang, Y Xiao, J He, L Zhang IEEE Transactions on Geoscience and Remote Sensing, 2023 | 10 | 2023 |
| A self-supervised remote sensing image fusion framework with dual-stage self-learning and spectral super-resolution injection J He, Q Yuan, J Li, Y Xiao, L Zhang ISPRS Journal of Photogrammetry and Remote Sensing 204, 131-144, 2023 | 10 | 2023 |
| Learning a local-global alignment network for satellite video super-resolution X Jin, J He, Y Xiao, Q Yuan IEEE Geoscience and Remote Sensing Letters 20, 1-5, 2023 | 9 | 2023 |
| Automated glacier extraction using a Transformer based deep learning approach from multi-sensor remote sensing imagery Y Peng, J He, Q Yuan, S Wang, X Chu, L Zhang ISPRS Journal of Photogrammetry and Remote Sensing 202, 303-313, 2023 | 7 | 2023 |
| An ensemble learning approach with multi-depth attention mechanism for road damage detection S Wang, Y Tang, X Liao, J He, H Feng, H Jiao, X Su, Q Yuan 2022 IEEE International Conference on Big Data (Big Data), 6439-6444, 2022 | 6 | 2022 |
| Spatial–Spectral fusion in different swath widths by a recurrent expanding residual convolutional neural network J He, J Li, Q Yuan, H Li, H Shen Remote Sensing 11 (19), 2203, 2019 | 6 | 2019 |
Qiangqiang YuanFull Professor in School of Geodesy and Geomatics, Wuhan universityVerified email at sgg.whu.edu.cn
