| Deep learning in environmental remote sensing: Achievements and challenges Q Yuan, H Shen, T Li, Z Li, S Li, Y Jiang, H Xu, W Tan, Q Yang, J Wang, ... Remote sensing of Environment 241, 111716, 2020 | 1196 | 2020 |
| Hyperspectral image restoration using low-rank matrix recovery H Zhang, W He, L Zhang, H Shen, Q Yuan IEEE transactions on geoscience and remote sensing 52 (8), 4729-4743, 2013 | 851 | 2013 |
| Land-cover classification with high-resolution remote sensing images using transferable deep models XY Tong, GS Xia, Q Lu, H Shen, S Li, S You, L Zhang Remote Sensing of Environment 237, 111322, 2020 | 781 | 2020 |
| Total-variation-regularized low-rank matrix factorization for hyperspectral image restoration W He, H Zhang, L Zhang, H Shen IEEE transactions on geoscience and remote sensing 54 (1), 178-188, 2015 | 622 | 2015 |
| Hyperspectral image denoising employing a spectral–spatial adaptive total variation model Q Yuan, L Zhang, H Shen IEEE Transactions on Geoscience and Remote Sensing 50 (10), 3660-3677, 2012 | 610 | 2012 |
| Image super-resolution: The techniques, applications, and future L Yue, H Shen, J Li, Q Yuan, H Zhang, L Zhang Signal processing 128, 389-408, 2016 | 574 | 2016 |
| A multiscale and multidepth convolutional neural network for remote sensing imagery pan-sharpening Q Yuan, Y Wei, X Meng, H Shen, L Zhang IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018 | 537 | 2018 |
| Missing information reconstruction of remote sensing data: A technical review H Shen, X Li, Q Cheng, C Zeng, G Yang, H Li, L Zhang IEEE Geoscience and Remote Sensing Magazine 3 (3), 61-85, 2015 | 495 | 2015 |
| Boosting the accuracy of multispectral image pansharpening by learning a deep residual network Y Wei, Q Yuan, H Shen, L Zhang IEEE Geoscience and Remote Sensing Letters 14 (10), 1795-1799, 2017 | 470 | 2017 |
| Hyperspectral image denoising employing a spatial–spectral deep residual convolutional neural network Q Yuan, Q Zhang, J Li, H Shen, L Zhang IEEE Transactions on Geoscience and Remote Sensing 57 (2), 1205-1218, 2018 | 442 | 2018 |
| A super-resolution reconstruction algorithm for surveillance images L Zhang, H Zhang, H Shen, P Li Signal Processing 90 (3), 848-859, 2010 | 412 | 2010 |
| Estimating Ground‐Level PM2.5 by Fusing Satellite and Station Observations: A Geo‐Intelligent Deep Learning Approach T Li, H Shen, Q Yuan, X Zhang, L Zhang Geophysical Research Letters 44 (23), 11,985-11,993, 2017 | 398 | 2017 |
| A MAP approach for joint motion estimation, segmentation, and super resolution H Shen, L Zhang, B Huang, P Li IEEE Transactions on Image processing 16 (2), 479-490, 2007 | 359 | 2007 |
| Long-term and fine-scale satellite monitoring of the urban heat island effect by the fusion of multi-temporal and multi-sensor remote sensed data: A 26-year case study of the … H Shen, L Huang, L Zhang, P Wu, C Zeng Remote sensing of environment 172, 109-125, 2016 | 352 | 2016 |
| Recovering missing pixels for Landsat ETM+ SLC-off imagery using multi-temporal regression analysis and a regularization method C Zeng, H Shen, L Zhang Remote Sensing of Environment 131, 182-194, 2013 | 323 | 2013 |
| Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors Z Li, H Shen, Q Cheng, Y Liu, S You, Z He ISPRS Journal of Photogrammetry and Remote Sensing 150, 197-212, 2019 | 319 | 2019 |
| An integrated framework for the spatio–temporal–spectral fusion of remote sensing images H Shen, X Meng, L Zhang IEEE Transactions on Geoscience and Remote Sensing 54 (12), 7135-7148, 2016 | 312 | 2016 |
| Review of the pansharpening methods for remote sensing images based on the idea of meta-analysis: Practical discussion and challenges X Meng, H Shen, H Li, L Zhang, R Fu Information Fusion 46, 102-113, 2019 | 309 | 2019 |
| A MAP-based algorithm for destriping and inpainting of remotely sensed images H Shen, L Zhang IEEE Transactions on Geoscience and Remote Sensing 47 (5), 1492-1502, 2008 | 308 | 2008 |
| Recovering quantitative remote sensing products contaminated by thick clouds and shadows using multitemporal dictionary learning X Li, H Shen, L Zhang, H Zhang, Q Yuan, G Yang IEEE Transactions on Geoscience and Remote Sensing 52 (11), 7086-7098, 2014 | 297 | 2014 |
Qiangqiang YuanFull Professor in School of Geodesy and Geomatics, Wuhan universityVahvistettu sähköpostiosoite verkkotunnuksessa sgg.whu.edu.cn
