| Research on correlation factor analysis and prediction method of overhead transmission line defect state based on association rule mining and RBF-SVM X Wang, Z Yan, Y Zeng, X Liu, X Peng, H Yuan Energy Reports 7, 359-368, 2021 | 234 | 2021 |
| Hyperspectral Image Classification Based on Three-Dimensional Scattering Wavelet Transform YY Tang, Y Lu, H Yuan IEEE T GRS, 2014 | 143 | 2014 |
| Manifold-Based Sparse Representation for Hyperspectral Image Classification YY Tang, H Yuan, L Li IEEE T GRS, 2014 | 133 | 2014 |
| Geometry constrained sparse coding for single image super-resolution X Lu, H Yuan, P Yan, Y Yuan, X Li 2012 IEEE Conference on Computer Vision and Pattern Recognition, 1648-1655, 2012 | 129 | 2012 |
| Resilience-constrained hourly unit commitment in electricity grids Y Wang, L Huang, M Shahidehpour, LL Lai, H Yuan, FY Xu IEEE Transactions on Power Systems 33 (5), 5604-5614, 2018 | 74 | 2018 |
| A robust correlation analysis framework for imbalanced and dichotomous data with uncertainty CS Lai, Y Tao, F Xu, WWY Ng, Y Jia, H Yuan, C Huang, LL Lai, Z Xu, ... Information Sciences 470, 58-77, 2019 | 73 | 2019 |
| Power market load forecasting on neural network with beneficial correlated regularization FY Xu, X Cun, M Yan, H Yuan, Y Wang, LL Lai IEEE Transactions on Industrial Informatics 14 (11), 5050-5059, 2018 | 55 | 2018 |
| Multi-view neural network ensemble for short and mid-term load forecasting CS Lai, Y Yang, K Pan, J Zhang, H Yuan, WWY Ng, Y Gao, Z Zhao, ... IEEE Transactions on Power Systems 36 (4), 2992-3003, 2020 | 52 | 2020 |
| Learning With Hypergraph for Hyperspectral Image Feature Extraction H Yuan, YY Tang IEEE GRSL, 2015 | 50 | 2015 |
| Spectral–spatial shared linear regression for hyperspectral image classification H Yuan, YY Tang IEEE transactions on cybernetics 47 (4), 934-945, 2016 | 46 | 2016 |
| A collaborative-competitive representation based classifier model H Yuan, X Li, F Xu, Y Wang, LL Lai, YY Tang Neurocomputing 275, 627-635, 2018 | 43 | 2018 |
| Hyperspectral image classification based on regularized sparse representation H Yuan, YY Tang, Y Lu, L Yang, H Luo IEEE journal of selected topics in applied earth observations and remote …, 2014 | 39 | 2014 |
| Load forecasting based on deep neural network and historical data augmentation CS Lai, Z Mo, T Wang, H Yuan, WWY Ng, LL Lai IET Generation, Transmission & Distribution 14 (24), 5927-5934, 2020 | 38 | 2020 |
| Low-rank matrix regression for image feature extraction and feature selection H Yuan, J Li, LL Lai, YY Tang Information Sciences 522, 214-226, 2020 | 37 | 2020 |
| Spectral-Spatial Classification of Hyperspectral Image Based on Discriminant Analysis H Yuan, YY Tang, Y Lu, L Yang, H Luo IEEE, 2014 | 35 | 2014 |
| Joint sparse matrix regression and nonnegative spectral analysis for two-dimensional unsupervised feature selection H Yuan, J Li, LL Lai, YY Tang Pattern Recognition 89, 119-133, 2019 | 34 | 2019 |
| Sparse Representation Based on Set-to-Set Distance for Hyperspectral Image Classification H Yuan, YY Tang IEEE, 2015 | 29 | 2015 |
| A novel state of health estimation method for lithium-ion batteries based on constant-voltage charging partial data and convolutional neural network SZ Chen, Z Liang, H Yuan, L Yang, F Xu, Y Fan Energy 283, 129103, 2023 | 27 | 2023 |
| Multi-view unsupervised feature selection with tensor low-rank minimization H Yuan, J Li, Y Liang, YY Tang Neurocomputing 487, 75-85, 2022 | 26 | 2022 |
| A constrained least squares regression model H Yuan, J Zheng, LL Lai, YY Tang Information Sciences 429, 247-259, 2018 | 24 | 2018 |