| Object-based mangrove species classification using unmanned aerial vehicle hyperspectral images and digital surface models J Cao, W Leng, K Liu, L Liu, Z He, Y Zhu Remote Sensing 10 (1), 89, 2018 | 261 | 2018 |
| Generative adversarial networks-based semi-supervised learning for hyperspectral image classification Z He, H Liu, Y Wang, J Hu Remote Sensing 9 (10), 1042, 2017 | 172 | 2017 |
| Exploring the potential of worldview-2 red-edge band-based vegetation indices for estimation of mangrove leaf area index with machine learning algorithms Y Zhu, K Liu, L Liu, SW Myint, S Wang, H Liu, Z He Remote Sensing 9 (10), 1060, 2017 | 109 | 2017 |
| Social media: New perspectives to improve remote sensing for emergency response J Li, Z He, J Plaza, S Li, J Chen, H Wu, Y Wang, Y Liu Proceedings of the IEEE 105 (10), 1900-1912, 2017 | 69 | 2017 |
| Boundary extension for Hilbert–Huang transform inspired by gray prediction model Z He, Y Shen, Q Wang Signal Processing 92 (3), 685-697, 2012 | 69 | 2012 |
| Multivariate gray model-based BEMD for hyperspectral image classification Z He, Q Wang, Y Shen, J Jin, Y Wang IEEE Transactions on Instrumentation and Measurement 62 (5), 889-904, 2013 | 52 | 2013 |
| Low-rank group inspired dictionary learning for hyperspectral image classification Z He, L Liu, R Deng, Y Shen Signal Processing 120, 209-221, 2016 | 51 | 2016 |
| Kernel sparse multitask learning for hyperspectral image classification with empirical mode decomposition and morphological wavelet-based features Z He, Q Wang, Y Shen, M Sun IEEE transactions on geoscience and remote sensing 52 (8), 5150-5163, 2013 | 51 | 2013 |
| Identifying mangrove species using field close-range snapshot hyperspectral imaging and machine-learning techniques J Cao, K Liu, L Liu, Y Zhu, J Li, Z He Remote Sensing 10 (12), 2047, 2018 | 49 | 2018 |
| Regularized multivariable grey model for stable grey coefficients estimation Z He, Y Shen, J Li, Y Wang Expert Systems with Applications 42 (4), 1806-1815, 2015 | 43 | 2015 |
| Optimized ensemble EMD-based spectral features for hyperspectral image classification Z He, Y Shen, Q Wang, Y Wang IEEE Transactions on Instrumentation and Measurement 63 (5), 1041-1056, 2014 | 35 | 2014 |
| Spectral-spatial hyperspectral image classification via SVM and superpixel segmentation Z He, Y Shen, M Zhang, Q Wang, Y Wang, R Yu 2014 IEEE International Instrumentation and Measurement Technology …, 2014 | 32 | 2014 |
| Three-dimensional empirical mode decomposition (TEMD): A fast approach motivated by separable filters Z He, J Li, L Liu, Y Shen Signal Processing 131, 307-319, 2017 | 31 | 2017 |
| Low-rank tensor learning for classification of hyperspectral image with limited labeled samples Z He, J Hu, Y Wang Signal Processing 145, 12-25, 2018 | 30 | 2018 |
| Learning group-based sparse and low-rank representation for hyperspectral image classification Z He, L Liu, S Zhou, Y Shen Pattern Recognition 60, 1041-1056, 2016 | 30 | 2016 |
| 3D-Gabor inspired multiview active learning for spectral-spatial hyperspectral image classification J Hu, Z He, J Li, L He, Y Wang Remote Sensing 10 (7), 1070, 2018 | 26 | 2018 |
| Kernel low-rank multitask learning in variational mode decomposition domain for multi-/hyperspectral classification Z He, J Li, K Liu, L Liu, H Tao IEEE Transactions on Geoscience and Remote Sensing 56 (7), 4193-4208, 2018 | 25 | 2018 |
| Hyperspectral image super-resolution inspired by deep Laplacian pyramid network Z He, L Liu Remote Sensing 10 (12), 1939, 2018 | 24 | 2018 |
| Object-oriented mangrove species classification using hyperspectral data and 3-D Siamese residual network Z He, Q Shi, K Liu, J Cao, W Zhan, B Cao IEEE Geoscience and Remote Sensing Letters 17 (12), 2150-2154, 2020 | 23 | 2020 |
| Discrete multivariate gray model based boundary extension for bi-dimensional empirical mode decomposition Z He, Q Wang, Y Shen, Y Wang Signal Processing 93 (1), 124-138, 2013 | 21 | 2013 |
