| EEG-Based Emotion Classification Using Deep Belief Networks WL Zheng, JY Zhu, Y Peng, BL Lu Multimedia and Expo (ICME), IEEE International Conference on, 1-6, 2014 | 407 | 2014 |
| Fine-grained leukocyte classification with deep residual learning for microscopic images F Qin, N Gao, Y Peng, Z Wu, S Shen, A Grudtsin Computer methods and programs in biomedicine 162, 243-252, 2018 | 138 | 2018 |
| Discriminative graph regularized extreme learning machine and its application to face recognition Y Peng, S Wang, X Long, BL Lu Neurocomputing 149, 340-353, 2015 | 116 | 2015 |
| Discriminative extreme learning machine with supervised sparsity preserving for image classification Y Peng, BL Lu Neurocomputing 261, 242-252, 2017 | 72 | 2017 |
| Graph regularized discriminative non-negative matrix factorization for face recognition X Long, H Lu, Y Peng, W Li Multimedia Tools and Applications 72, 2679-2699, 2014 | 68 | 2014 |
| GFIL: A unified framework for the importance analysis of features, frequency bands and channels in EEG-based emotion recognition Y Peng, F Qin, W Kong, Y Ge, F Nie, A Cichocki IEEE Transactions on Cognitive and Developmental Systems 14 (3), 935-947, 2022 | 54 | 2022 |
| Discriminative manifold extreme learning machine and applications to image and EEG signal classification Y Peng, BL Lu Neurocomputing 174, 265-277, 2016 | 46 | 2016 |
| Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning Y Peng, BL Lu, S Wang Neural Networks 65, 1-17, 2015 | 45 | 2015 |
| Hybrid learning clonal selection algorithm Y Peng, BL Lu Information Sciences 296, 128-146, 2015 | 45 | 2015 |
| An unsupervised discriminative extreme learning machine and its applications to data clustering Y Peng, WL Zheng, BL Lu Neurocomputing 174, 250-264, 2016 | 44 | 2016 |
| EEG-based emotion recognition using discriminative graph regularized extreme learning machine JY Zhu, WL Zheng, Y Peng, BL Lu Neural Networks (IJCNN), 2014 International Joint Conference on, 525-532, 2014 | 37 | 2014 |
| A joint optimization framework to semi-supervised RVFL and ELM networks for efficient data classification Y Peng, Q Li, W Kong, F Qin, J Zhang, A Cichocki Applied Soft Computing 97, 106756, 2020 | 34 | 2020 |
| Fuzzy graph clustering Y Peng, X Zhu, F Nie, W Kong, Y Ge Information Sciences 571, 38-49, 2021 | 33 | 2021 |
| Orthogonal extreme learning machine for image classification Y Peng, W Kong, B Yang Neurocomputing 266, 458--464, 2017 | 30 | 2017 |
| OGSSL: A Semi-Supervised Classification Model Coupled with Optimal Graph Learning for EEG Emotion Recognition Y Peng, F Jin, W Kong, F Nie, BL Lu, A Cichocki IEEE Transactions on Neural Systems and Rehabilitation Engineering 30, 1288-1297, 2022 | 29 | 2022 |
| A hierarchical particle swarm optimizer with latin sampling based memetic algorithm for numerical optimization Y Peng, BL Lu Applied Soft Computing 13 (5), 2823-2836, 2013 | 29 | 2013 |
| Multi-scale frequency bands ensemble learning for EEG-based emotion recognition F Shen, Y Peng, W Kong, G Dai Sensors 21 (4), 1262, 2021 | 27 | 2021 |
| Recognizing slow eye movement for driver fatigue detection with machine learning approach Y Jiao, Y Peng, BL Lu, X Chen, S Chen, C Wang 2014 International Joint Conference on Neural Networks (IJCNN), 4035-4041, 2014 | 27 | 2014 |
| Self-weighted semi-supervised classification for joint EEG-based emotion recognition and affective activation patterns mining Y Peng, W Kong, F Qin, F Nie, J Fang, BL Lu, A Cichocki IEEE Transactions on Instrumentation and Measurement 70, 1-11, 2021 | 26 | 2021 |
| Recurrent neural network from adder’s perspective: Carry-lookahead RNN H Jiang, F Qin, J Cao, Y Peng, Y Shao Neural Networks 144, 297-306, 2021 | 25 | 2021 |
wanzeng kongProf. College of Computer Science, Hangzhou Dianzi University在 hdu.edu.cn 的电子邮件经过验证
