Ntire 2020 challenge on spectral reconstruction from an rgb image B Arad, R Timofte, O Ben-Shahar, YT Lin, GD Finlayson Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 131 | 2020 |
Hyperspectral image super-resolution using deep convolutional neural network Y Li, J Hu, X Zhao, W Xie, JJ Li Neurocomputing 266, 29-41, 2017 | 122 | 2017 |
Classification of hyperspectral imagery using a new fully convolutional neural network J Li, X Zhao, Y Li, Q Du, B Xi, J Hu IEEE Geoscience and Remote Sensing Letters 15 (2), 292-296, 2018 | 110 | 2018 |
Hyperspectral classification based on texture feature enhancement and deep belief networks J Li, B Xi, Y Li, Q Du, K Wang Remote Sensing 10 (3), 396, 2018 | 73 | 2018 |
Adaptive weighted attention network with camera spectral sensitivity prior for spectral reconstruction from RGB images J Li, C Wu, R Song, Y Li, F Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 48 | 2020 |
Hyperspectral pansharpening using deep prior and dual attention residual network Y Zheng, J Li, Y Li, J Guo, X Wu, J Chanussot IEEE transactions on geoscience and remote sensing 58 (11), 8059-8076, 2020 | 45 | 2020 |
Hyperspectral image classification with imbalanced data based on orthogonal complement subspace projection J Li, Q Du, Y Li, W Li IEEE Transactions on Geoscience and Remote Sensing 56 (7), 3838-3851, 2018 | 45 | 2018 |
Hyperspectral image super-resolution by band attention through adversarial learning J Li, R Cui, B Li, R Song, Y Li, Y Dai, Q Du IEEE Transactions on Geoscience and Remote Sensing 58 (6), 4304-4318, 2020 | 41 | 2020 |
HPGAN: Hyperspectral pansharpening using 3-D generative adversarial networks W Xie, Y Cui, Y Li, J Lei, Q Du, J Li IEEE Transactions on Geoscience and Remote Sensing 59 (1), 463-477, 2020 | 33 | 2020 |
Deep kernel extreme-learning machine for the spectral–spatial classification of hyperspectral imagery J Li, B Xi, Q Du, R Song, Y Li, G Ren Remote Sensing 10 (12), 2036, 2018 | 28 | 2018 |
Optimizing extreme learning machine for hyperspectral image classification J Li, Q Du, W Li, Y Li Journal of Applied Remote Sensing 9 (1), 097296, 2015 | 28 | 2015 |
Weakly supervised low-rank representation for hyperspectral anomaly detection W Xie, X Zhang, Y Li, J Lei, J Li, Q Du IEEE Transactions on Cybernetics 51 (8), 3889-3900, 2021 | 26 | 2021 |
An efficient radial basis function neural network for hyperspectral remote sensing image classification J Li, Q Du, Y Li Soft Computing 20 (12), 4753-4759, 2016 | 26 | 2016 |
Local spectral similarity preserving regularized robust sparse hyperspectral unmixing J Li, Y Li, R Song, S Mei, Q Du IEEE Transactions on Geoscience and Remote Sensing 57 (10), 7756-7769, 2019 | 23 | 2019 |
Deep fully convolutional regression networks for single image haze removal X Zhao, K Wang, Y Li, J Li 2017 IEEE Visual Communications and Image Processing (VCIP), 1-4, 2017 | 22 | 2017 |
Deep residual learning for boosting the accuracy of hyperspectral pansharpening Y Zheng, J Li, Y Li, K Cao, K Wang IEEE Geoscience and Remote Sensing Letters 17 (8), 1435-1439, 2019 | 20 | 2019 |
Hybrid 2-D–3-D deep residual attentional network with structure tensor constraints for spectral super-resolution of RGB images J Li, C Wu, R Song, W Xie, C Ge, B Li, Y Li IEEE Transactions on Geoscience and Remote Sensing 59 (3), 2321-2335, 2020 | 18 | 2020 |
Multiscale context-aware ensemble deep KELM for efficient hyperspectral image classification B Xi, J Li, Y Li, R Song, W Sun, Q Du IEEE Transactions on Geoscience and Remote Sensing 59 (6), 5114-5130, 2020 | 17 | 2020 |
Hyperspectral image super-resolution with 1D–2D attentional convolutional neural network J Li, R Cui, B Li, R Song, Y Li, Q Du Remote Sensing 11 (23), 2859, 2019 | 17 | 2019 |
Class feature weighted hyperspectral image classification S Zhong, CI Chang, J Li, X Shang, S Chen, M Song, Y Zhang IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2019 | 16 | 2019 |