| A review on the attention mechanism of deep learning Z Niu, G Zhong, H Yu Neurocomputing 452, 48-62, 2021 | 1939 | 2021 |
| Prediction of sea surface temperature using long short-term memory Q Zhang, H Wang, J Dong, G Zhong, X Sun IEEE geoscience and remote sensing letters 14 (10), 1745-1749, 2017 | 414 | 2017 |
| Stock market prediction based on generative adversarial network K Zhang, G Zhong, J Dong, S Wang, Y Wang Procedia computer science 147, 400-406, 2019 | 318 | 2019 |
| An overview on data representation learning: From traditional feature learning to recent deep learning G Zhong, LN Wang, X Ling, J Dong The Journal of Finance and Data Science 2 (4), 265-278, 2016 | 258 | 2016 |
| From shallow feature learning to deep learning: Benefits from the width and depth of deep architectures G Zhong, X Ling, LN Wang Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 9 (1 …, 2019 | 101 | 2019 |
| Improving short text classification by learning vector representations of both words and hidden topics H Zhang, G Zhong Knowledge-Based Systems 102, 76-86, 2016 | 95 | 2016 |
| Change detection in SAR images based on deep semi-NMF and SVD networks F Gao, X Liu, J Dong, G Zhong, M Jian Remote Sensing 9 (5), 435, 2017 | 56 | 2017 |
| Generative adversarial networks with decoder–encoder output noises G Zhong, W Gao, Y Liu, Y Yang, DH Wang, K Huang Neural Networks 127, 19-28, 2020 | 45 | 2020 |
| Banzhaf random forests: Cooperative game theory based random forests with consistency J Sun, G Zhong, K Huang, J Dong Neural Networks 106, 20-29, 2018 | 45 | 2018 |
| Reducing and stretching deep convolutional activation features for accurate image classification G Zhong, S Yan, K Huang, Y Cai, J Dong Cognitive Computation 10, 179-186, 2018 | 41 | 2018 |
| Random shapley forests: cooperative game-based random forests with consistency J Sun, H Yu, G Zhong, J Dong, S Zhang, H Yu IEEE transactions on cybernetics 52 (1), 205-214, 2020 | 40 | 2020 |
| Low-rank tensor learning with discriminant analysis for action classification and image recovery C Jia, G Zhong, Y Fu Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 39 | 2014 |
| Error-correcting output codes based ensemble feature extraction G Zhong, CL Liu Pattern Recognition 46 (4), 1091-1100, 2013 | 39 | 2013 |
| Gaussian process latent random field G Zhong, WJ Li, DY Yeung, X Hou, CL Liu Proceedings of the AAAI conference on artificial intelligence 24 (1), 679-684, 2010 | 35 | 2010 |
| Recurrent attention unit: A new gated recurrent unit for long-term memory of important parts in sequential data Z Niu, G Zhong, G Yue, LN Wang, H Yu, X Ling, J Dong Neurocomputing 517, 1-9, 2023 | 34 | 2023 |
| Deep hashing learning networks G Zhong, H Xu, P Yang, S Wang, J Dong 2016 International Joint Conference on Neural Networks (IJCNN), 2236-2243, 2016 | 34 | 2016 |
| Adaptive error-correcting output codes G Zhong, M Cheriet Twenty-Third International Joint Conference on Artificial Intelligence, 2013 | 34 | 2013 |
| Low rank metric learning with manifold regularization G Zhong, K Huang, CL Liu 2011 IEEE 11th International Conference on Data Mining, 1266-1271, 2011 | 33 | 2011 |
| Comparative analysis of three methods for HYSPLIT atmospheric trajectories clustering L Cui, X Song, G Zhong Atmosphere 12 (6), 698, 2021 | 31 | 2021 |
| Marginal deep architecture: Stacking feature learning modules to build deep learning models G Zhong, K Zhang, H Wei, Y Zheng, J Dong Ieee Access 7, 30220-30233, 2019 | 30 | 2019 |
Junyu DongOcean University of ChinaVerified email at ouc.edu.cn
