| Multiple neural networks switched prediction for landslide displacement C Lian, Z Zeng, W Yao, H Tang Engineering geology 186, 91-99, 2015 | 139 | 2015 |
| Pixel-wise regression using U-Net and its application on pansharpening W Yao, Z Zeng, C Lian, H Tang Neurocomputing 312, 364-371, 2018 | 133 | 2018 |
| Displacement prediction model of landslide based on a modified ensemble empirical mode decomposition and extreme learning machine C Lian, Z Zeng, W Yao, H Tang Natural hazards 66, 759-771, 2013 | 116 | 2013 |
| Ensemble of extreme learning machine for landslide displacement prediction based on time series analysis C Lian, Z Zeng, W Yao, H Tang Neural Computing and Applications 24, 99-107, 2014 | 111 | 2014 |
| Extreme learning machine for the displacement prediction of landslide under rainfall and reservoir level C Lian, Z Zeng, W Yao, H Tang Stochastic environmental research and risk assessment 28, 1957-1972, 2014 | 80 | 2014 |
| Landslide displacement prediction with uncertainty based on neural networks with random hidden weights C Lian, Z Zeng, W Yao, H Tang, CLP Chen IEEE transactions on neural networks and learning systems 27 (12), 2683-2695, 2016 | 71 | 2016 |
| Constructing prediction intervals for landslide displacement using bootstrapping random vector functional link networks selective ensemble with neural networks switched C Lian, L Zhu, Z Zeng, Y Su, W Yao, H Tang Neurocomputing 291, 1-10, 2018 | 58 | 2018 |
| Training enhanced reservoir computing predictor for landslide displacement W Yao, Z Zeng, C Lian, H Tang Engineering Geology 188, 101-109, 2015 | 58 | 2015 |
| Landslide displacement interval prediction using lower upper bound estimation method with pre-trained random vector functional link network initialization C Lian, Z Zeng, X Wang, W Yao, Y Su, H Tang Neural Networks 130, 286-296, 2020 | 43 | 2020 |
| Prediction intervals for landslide displacement based on switched neural networks C Lian, CLP Chen, Z Zeng, W Yao, H Tang IEEE Transactions on Reliability 65 (3), 1483-1495, 2016 | 35 | 2016 |
| A multi-view multi-scale neural network for multi-label ECG classification S Yang, C Lian, Z Zeng, B Xu, J Zang, Z Zhang IEEE Transactions on Emerging Topics in Computational Intelligence, 2023 | 29 | 2023 |
| Generating probabilistic predictions using mean-variance estimation and echo state network W Yao, Z Zeng, C Lian Neurocomputing 219, 536-547, 2017 | 27 | 2017 |
| Displacement prediction of landslide based on PSOGSA-ELM with mixed kernel C Lian, Z Zeng, W Yao, H Tang 2013 Sixth International Conference on Advanced Computational Intelligence …, 2013 | 27 | 2013 |
| Semi-supervised low-rank semantics grouping for zero-shot learning B Xu, Z Zeng, C Lian, Z Ding IEEE Transactions on Image Processing 30, 2207-2219, 2021 | 23 | 2021 |
| Generative mixup networks for zero-shot learning B Xu, Z Zeng, C Lian, Z Ding IEEE Transactions on Neural Networks and Learning Systems, 2022 | 22 | 2022 |
| A broad learning system with ensemble and classification methods for multi-step-ahead wind speed prediction L Zhu, C Lian, Z Zeng, Y Su Cognitive Computation 12, 654-666, 2020 | 20 | 2020 |
| Few-shot domain adaptation via mixup optimal transport B Xu, Z Zeng, C Lian, Z Ding IEEE Transactions on Image Processing 31, 2518-2528, 2022 | 19 | 2022 |
| ClusterCNN: Clustering-based feature learning for hyperspectral image classification W Yao, C Lian, L Bruzzone IEEE Geoscience and Remote Sensing Letters 18 (11), 1991-1995, 2020 | 19 | 2020 |
| Multimodal multi-instance learning for long-term ECG classification H Han, C Lian, Z Zeng, B Xu, J Zang, C Xue Knowledge-Based Systems 270, 110555, 2023 | 16 | 2023 |
| Ensembles of echo state networks for time series prediction W Yao, Z Zeng, C Lian, H Tang 2013 Sixth International Conference on Advanced Computational Intelligence …, 2013 | 16 | 2013 |
