Yong Peng (彭勇)
Yong Peng (彭勇)
IEEE Senior Member, Professor, Hangzhou Dianzi University
Verified email at - Homepage
Cited by
Cited by
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
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
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
Discriminative extreme learning machine with supervised sparsity preserving for image classification
Y Peng, BL Lu
Neurocomputing 261, 242-252, 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
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
Discriminative manifold extreme learning machine and applications to image and EEG signal classification
Y Peng, BL Lu
Neurocomputing 174, 265-277, 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
Hybrid learning clonal selection algorithm
Y Peng, BL Lu
Information Sciences 296, 128-146, 2015
An unsupervised discriminative extreme learning machine and its applications to data clustering
Y Peng, WL Zheng, BL Lu
Neurocomputing 174, 250-264, 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
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
Fuzzy graph clustering
Y Peng, X Zhu, F Nie, W Kong, Y Ge
Information Sciences 571, 38-49, 2021
Orthogonal extreme learning machine for image classification
Y Peng, W Kong, B Yang
Neurocomputing 266, 458--464, 2017
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
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
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
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
Multi-scale frequency bands ensemble learning for EEG-based emotion recognition
F Shen, Y Peng, W Kong, G Dai
Sensors 21 (4), 1262, 2021
Weighted extreme learning machine for P300 detection with application to brain computer interface
W Kong, S Guo, Y Long, Y Peng, H Zeng, X Zhang, J Zhang
Journal of Ambient Intelligence and Humanized Computing 14, 15545-15555, 2018
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