| Deep learning for remote sensing data: A technical tutorial on the state of the art L Zhang, L Zhang, B Du IEEE Geoscience and Remote Sensing Magazine 4 (2), 22-40, 2016 | 915 | 2016 |
| Saliency-guided unsupervised feature learning for scene classification F Zhang, B Du, L Zhang IEEE Transactions on Geoscience and Remote Sensing 53 (4), 2175-2184, 2014 | 405 | 2014 |
| Scene classification via a gradient boosting random convolutional network framework F Zhang, B Du, L Zhang IEEE Transactions on Geoscience and Remote Sensing 54 (3), 1793-1802, 2015 | 282 | 2015 |
| Stacked convolutional denoising auto-encoders for feature representation B Du, W Xiong, J Wu, L Zhang, L Zhang, D Tao IEEE transactions on cybernetics 47 (4), 1017-1027, 2016 | 263 | 2016 |
| Ensemble manifold regularized sparse low-rank approximation for multiview feature embedding L Zhang, Q Zhang, L Zhang, D Tao, X Huang, B Du Pattern Recognition 48 (10), 3102-3112, 2015 | 257 | 2015 |
| Random-selection-based anomaly detector for hyperspectral imagery B Du, L Zhang IEEE Transactions on Geoscience and Remote sensing 49 (5), 1578-1589, 2010 | 244 | 2010 |
| A discriminative metric learning based anomaly detection method B Du, L Zhang IEEE Transactions on Geoscience and Remote Sensing 52 (11), 6844-6857, 2014 | 235 | 2014 |
| Weakly supervised learning based on coupled convolutional neural networks for aircraft detection F Zhang, B Du, L Zhang, M Xu IEEE Transactions on Geoscience and Remote Sensing 54 (9), 5553-5563, 2016 | 153 | 2016 |
| Simultaneous spectral-spatial feature selection and extraction for hyperspectral images L Zhang, Q Zhang, B Du, X Huang, YY Tang, D Tao IEEE Transactions on Cybernetics 48 (1), 16-28, 2016 | 150 | 2016 |
| A low-rank and sparse matrix decomposition-based Mahalanobis distance method for hyperspectral anomaly detection Y Zhang, B Du, L Zhang, S Wang IEEE Transactions on Geoscience and Remote Sensing 54 (3), 1376-1389, 2015 | 149 | 2015 |
| Target detection based on a dynamic subspace B Du, L Zhang Pattern Recognition 47 (1), 344-358, 2014 | 148 | 2014 |
| A sparse representation-based binary hypothesis model for target detection in hyperspectral images Y Zhang, B Du, L Zhang IEEE Transactions on Geoscience and Remote Sensing 53 (3), 1346-1354, 2014 | 132 | 2014 |
| Feature learning using spatial-spectral hypergraph discriminant analysis for hyperspectral image F Luo, B Du, L Zhang, L Zhang, D Tao IEEE transactions on cybernetics 49 (7), 2406-2419, 2018 | 129 | 2018 |
| Hyperspectral remote sensing image subpixel target detection based on supervised metric learning L Zhang, L Zhang, D Tao, X Huang, B Du IEEE transactions on geoscience and remote sensing 52 (8), 4955-4965, 2013 | 121 | 2013 |
| Exploring representativeness and informativeness for active learning B Du, Z Wang, L Zhang, L Zhang, W Liu, J Shen, D Tao IEEE transactions on cybernetics 47 (1), 14-26, 2015 | 120 | 2015 |
| Beyond the sparsity-based target detector: A hybrid sparsity and statistics-based detector for hyperspectral images B Du, Y Zhang, L Zhang, D Tao IEEE Transactions on Image Processing 25 (11), 5345-5357, 2016 | 119 | 2016 |
| An endmember dissimilarity constrained non-negative matrix factorization method for hyperspectral unmixing N Wang, B Du, L Zhang IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2013 | 118 | 2013 |
| Slow feature analysis for change detection in multispectral imagery C Wu, B Du, L Zhang IEEE Transactions on Geoscience and Remote Sensing 52 (5), 2858-2874, 2013 | 112 | 2013 |
| PLTD: Patch-based low-rank tensor decomposition for hyperspectral images B Du, M Zhang, L Zhang, R Hu, D Tao IEEE Transactions on Multimedia 19 (1), 67-79, 2016 | 109 | 2016 |
| Hyperspectral image unsupervised classification by robust manifold matrix factorization L Zhang, L Zhang, B Du, J You, D Tao Information Sciences 485, 154-169, 2019 | 108 | 2019 |
Lefei ZhangSchool of Computer Science, Wuhan UniversityVerified email at whu.edu.cn
