Yong Peng

SCI源刊论文列表:
[1] Bowen Pang, Yong Peng, Jian Gao, Wanzeng Kong. Semi-supervised bipartite graph construction with active EEG sample selection for emotion recognition. Medical & Biological Engineering & Computing, vol. 62, 2805–2824, 2024.
[2] Xing Li, Yikai Zhang, Yong Peng, Wanzeng Kong. Enhanced performance of EEG-based brain-computer interfaces by joint sample and feature importance assessment. Health Information Science and Systems, 12(1): 9, 2024.
[3] Keding Chen, Yong Peng, Feiping Nie, and Wanzeng Kong. Soft label guided unsupervised discriminative sparse subspace feature selection. Journal of Classification, 41(1): 129-157, 2024.
[4] Ting Wang, Jianpeng Tang, Xugang Xi, Yong Peng, Maofeng Wang, Lihua Li. Corticomuscular coupling analysis in stroke rehabilitation based on variational mode decomposition-transfer entropy. IEEE Transactions on Neural Systems and Rehabilitation Engineering, DOI: 10.1109/TNSRE.2024.3436077, 2024.
[5] Bing Yang, Xueqin Xiang, Wangzeng Kong, Jianhai Zhang, Yong Peng. DMF-GAN: Deep multimodal fusion generative adversarial networks for text-to-image synthesis. IEEE Transactions on Multimedia, 26: 6956-6967, 2024.
[6] Feiwei Qin, Kang Yan, Changmiao Wang, Ruiquan Ge, Yong Peng, Kai Zhang. LKFormer: large kernel transformer for infrared image super-resolution. Multimedia Tools and Applications, 83(28): 72063-72077, 2024.
[7] Honggang Liu, Xuanyu Jin, Dongjun Liu, Wanzeng Kong, Jiajia Tang, Yong Peng. Affective EEG-based cross-session person identification using hierarchical graph embedding. Cognitive Neurodynamics, DOI:10.1007/s11571-024-10132-x, 2024.
[8] Xuanyu Jin, Xinyu Yang, Wanzeng Kong, Li Zhu, Jiajia Tang, Yong Peng, Yu Ding, Qibin Zhao. TSFAN: tensorized spatial-frequency attention network with domain adaptation for cross-session EEG-based biometric recognition. Journal of Neural Engineering, vol. 21, ID 046005, 2024.
[9] Yifei Chen, Chenyan Zhang, Ben Chen, Yiyu Huang, Yifei Sun, Changmiao Wang, Feiwei Qin, Yong Peng, Yu Gao. Accurate leukocyte detection based on deformable-DETR and multi-level feature fusion for aiding diagnosis of blood diseases. Computers in Biology and Medicine, vol. 170, ID 107917, 2024.
[10] Qi Zhu, Yong Peng. Semi-supervised kernel discriminative low-rank regression for data classification. International Arab Journal of Information Technology, 21(5): 800-815, 2024.
[11] Diankun Chen, Feiwei Qin, Ruiquan Ge, Yong Peng, Changmiao Wang. ID-UNet: a densly connected Unet architecture for infrared small target segmentation. Alexandria Engineering Journal, accepted, 2024.
[12] Yong Peng, Honggang Liu, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki. Joint EEG feature transfer and semi-supervised cross-subject emotion recognition, IEEE Transactions on Industrial Informatics, 19(7): 8104-8115, 2023.
[13] Yong Peng, Wenna Huang, Wanzeng Kong, Feiping Nie, and Bao-Liang Lu. JGSED: an end-to-end spectral clustering model for joint graph Construction, spectral embedding and discretization. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(6): 1687-1701, 2023.
[14] Yong Peng, Honggang Liu, Junhua Li, Jun Huang, Bao-Liang Lu, and Wanzeng Kong. Cross-session emotion recognition by joint label-common and label-specific EEG features exploration. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, 759-768, 2023.
[15] Yong Peng, Keding Chen, Feiping Nie, Bao-Liang Lu, Wanzeng Kong. Two-dimensional embedded fuzzy data clustering. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(4):1263-1275, 2023.
[16] Li Zhu, Youyang Liu, Riheng Liu, Yong Peng, Junhua Li, and Wanzeng Kong. Decoding multi-brain motor imagery from EEG using coupling feature extraction and few-shot learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, pages 4683-4692, 2023.
[17] Fengzhe Jin, Yong Peng, Feiwei Qin, Junhua Li, and Wanzeng Kong. Graph adaptive semi-supervised discriminative subspace learning for EEG emotion recognition. Journal of King Saud University-Computer and Information Sciences, 35(8), ID 101648, 2023.
[18] Yikai Zhang, Yong Peng, Junhua Li, and Wanzeng Kong. SIFIAE: an adaptive emotion recognition model with EEG feature-label inconsistency consideration. Journal of Neuroscience Methods, 395, ID 109909, 2023.
[19] Tianhui Sha, Yikai Zhang, Yong Peng, and Wanzeng Kong. Semi-supervised regression with adaptive graph learning for EEG-based emotion recognition. Mathematical Biosciences and Engineering, 20(6): 11379-11402, 2023.
[20] Tianhui Sha, and Yong Peng. Orthogonal semi-supervised regression with adaptive label dragging for cross-session EEG emotion recognition. Journal of King Saud University-Computer and Information Sciences, 35(4): 139-151, 2023.
[21] Jin Cao, Ran Xu, Xinnan Lin, Feiwei Qin, Yong Peng, and Yanli Shao. Adaptive receptive field U-shaped temporal convolutional network for vulgar action detection. Neural Computing & Applications, 35(13): 9593-9606, 2023.
[22] Jiajia Tang, Dongjun Liu, Xuanyu Jin, Yong Peng, Qibin Zhao, Yu Ding, Wanzeng Kong. BAFN: bi-direction attention based fusion network for multimodal sentiment analysis. IEEE Transactions on Circuits and Systems for Video Technology, 33(4): 1966-1978, 2023.
[23] Haiting Jiang, Fangyao Shen, Lina Chen, Yong Peng, Hongjie Guo, and Hong Gao. Joint domain symmetry and predictive balance for cross-dataset EEG emotion recognition. Journal of Neuroscience Methods, vol. 400, ID 109978, 2023.
[24] Ben Chen, Feiwei Qin, Yanli Shao, Jin Cao, Yong Peng, and Ruiquan Ge. Fine-grained imbalanced leukocyte classification with global-local attention transformer. Journal of King Saud University-Computer and Information Sciences, 35(8), ID 101661, 2023.
[25] Wanzeng Kong, Shijie Guo, Yanfang Long, Yong Peng, Hong Zeng, Xinyu Zhang, Jianhai Zhang. Weighted extreme learning machine for P300 detection with application to brain computer interface. Journal of Ambient Intelligence and Humanized Computing, vol. 15, 15545-15555, 2023.
[26] Yong Peng, Wenjuan Wang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki. Joint feature adaptation and graph adaptive label propagation for cross-subject emotion recognition from EEG signals. IEEE Transactions on Affective Computing, 13(4): 1941-1958, 2022.
[27] Yong Peng, Fengzhe Jin, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki. OGSSL: a semi-supervised classification model coupled with optimal graph learning for EEG emotion recognition. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30, 1288-1297, 2022.
[28] Yong Peng, Yikai Zhang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki. S3LRR: a unified model for joint discriminative subspace identification and semi-supervised EEG emotion recognition. IEEE Transactions on Instrumentation and Measurement, 71, Article ID 2507313, 2022.
[29] Yong Peng, Feiwei Qin, Wanzeng Kong, Feiping Nie, Yuan Ge, Andrzej Cichocki. GFIL: a unified framework for the analysis of features, frequency bands, channels in EEG-based emotion recognition. IEEE Transactions on Cognitive and Developmental Systems, 14(3): 935-947, 2022. (ESI高被引论文)
[30] Xing Li, Fangyao Shen, Yong Peng, Wanzeng Kong, Bao-Liang Lu. Efficient Sample and Feature Importance Mining in Semi-supervised EEG Emotion Recognition. IEEE Transactions on Circuits and Systems-II: Express Briefs, 69(7): 3349–3353, 2022.
[31] Ruiqi Guo, Yong Peng, Wanzeng Kong, Fan Li. A semi-supervised label distribution learning model with label correlations and data manifold exploration. Journal of King-Saud University-Computer and Information Sciences, 34(10 Part B): 10094-10108, 2022.
[32] Yikai Zhang, Ruiqi Guo, Yong Peng, Wanzeng Kong, Feiping Nie, Bao-Liang Lu. An auto-weighting incremental random vector functional link network for EEG-based driving fatigue detection. IEEE Transactions on Instrumentation and Measurement, vol. 71, Article ID 4010014, 2022.
[33] Wenzheng Li, Yong Peng. Transfer EEG emotion recognition by combining semi-supervised regression with bipartite graph label propagation. Systems, 10(4), Article ID 111 , 2022.
[34] Ziyuan Chen, Shuzhe Duan, Yong Peng. EEG-based emotion recognition by retargeted semi-supervised regression with robust weights. Systems, 10(6), Article ID 236, 2022. [35] Fangyao Shen, Yong Peng, Guojun Dai, Bao-Liang Lu, Wanzeng Kong. Coupled projection transfer metric learning for cross-session emotion recognition from EEG. Systems, 10(2), Article ID 47, 2022.
[36] Bing Yang, Xueqin Xiang, Wanzeng Kong, Yong Peng, Jinliang Yao. Adaptive multi-task learning using lagrange multiplier for automatic art analysis. Multimedia Tools and Applications, 81(3): 3715-3733, 2022.
[37] Meie Fang, Zhuxin Jin, Feiwei Qin, Yong Peng, Chao Jiang, Zhigeng Pan. Re-transfer learning and multi-modal learning assisted early diagnosis Alzheimer’s disease. Multimedia Tools and Applications, 81(20): 29159-29175, 2022.
[38] Senwei Xu, Li Zhu, Wanzeng Kong, Yong Peng, Hua Hu, Jianting Cao. A novel classification method for EEG-based motor imagery with narrow band spatial filters and deep convolutional neural network. Cognitive Neurodynamics, 16, 379-389, 2022.
[39] Yong Peng, Wanzeng Kong, Feiwei Qin, Feiping Nie, Jinglong Fang, Bao-Liang Lu, Andrzej Cichocki. Self-weighted semi-supervised classification for joint EEG-based emotion recognition and affective activation patterns mining. IEEE Transactions on Instrumentation and Measurement, 70, Article ID 2517111, 2021.
[40] Yong Peng, Xin Zhu, Feiping Nie, Wanzeng Kong, Yuan Ge. Fuzzy graph clustering. Information Sciences, 571: 38-49, 2021.
[41] Yong Peng, Yikai Zhang, Feiwei Qin, Wanzeng Kong. Joint non-negative and fuzzy coding with graph regularization for efficient data clustering. Egyptian Informatics Journal, 22(1): 91-100, 2021.
[42] Wenna Huang, Yong Peng, Yuan Ge, Wanzeng Kong. A new kmeans formulation and its generalization achieved by joint spectral embedding and rotation. PeerJ Computer Science, 7, Article ID: e450, 2021.
[43] Yikai Zhang, Yong Peng, Hongyu Bian, Yuan Ge, Feiwei Qin, Wanzeng Kong. Auto-weighted concept factorization for joint feature map and data representation learning. Journal of Intelligent & Fuzzy Systems, 41(1): 69-81, 2021.
[44] Xuanyu Jin, Jiajia Tang, Xianghao Kong, Yong Peng, Jianting Cao, Qibin Zhao, Wanzeng Kong. CTNN: a convolutional tensor-train neural network for multi-task brainprint recognition. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 103-112, 2021.
[45] Haowei Jiang, Feiwei Qin, Jin Cao, Yong Peng, Yanli Shao. Recurrent Neural Network from Adder’s Perspective: Carry-lookahead RNN. Neural Networks, 144, 297-306, 2021.
[46] Xinnan Lin, Feiwei Qin, Yong Peng, Yanli Shao. Fine-Grained Pornographic Image Recognition with Multiple Feature Fusion Transfer Learning. International Journal of Machine Learning and Cybernetics, 12, 73-86, 2021.
[47] Fangyao Shen, Yong Peng, Wanzeng Kong, Guojun Dai. Multi-scale frequency bands ensemble learning for EEG-based emotion recognition. Sensors, 21(4), 1262, 2021.
[48] Yuxuan Zhu, Yong Peng, Yang Song, Kenji Ozawa, Wanzeg Kong. RAMST-CNN: A residual and multiscale spatio-temporal convolution neural network for personal identification with EEG. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E104-A, No.2, pp.563-571, 2021.
[49] Yong Peng, Qingxi Li, Wanzeng Kong, Feiwei Qin, Jianhai Zhang, Andrzej Cichocki. A joint optimization framework to semi-supervised RVFL and ELM networks for efficient data classification. Applied Soft Computing, volume 97, Part A, Article ID 106756, 2020.
[50] Yong Peng, Leijie Zhang, Wanzeng Kong, Feiwei Qin, Jianhai Zhang. Joint low-rank representation and spectral regression for robust subspace learning. Knowledge-Based Systems, 195, 105723, 2020.
[51] Yong Peng, Leijie Zhang, Wanzeng Kong, Feiwei Qin, Jianhai Zhang. Low rank spectral regression via matrix factorization for efficient subspace learning. Journal of Intelligent & Fuzzy Systems, 39(3): 3401-3412, 2020.
[52] Qinghao Ye, Daijian Tu, Feiwei Qin, Zizhao Wu, Yong Peng, Shuying Shen. Dual attention based fine-grained leukocyte recognition for imbalanced microscopic images. Journal of Intelligent & Fuzzy Systems, 37(5): 6971-6982, 2019.
[53] Yong Peng, Wanzeng Kong, Feiwei Qin, Feiping Nie. Manifold adaptive kernelized low-rank representation for semi-supervised image classification. Complexity, Volume 2018 (2018), Article ID 2857594, 2018.
[54] Feiwei Qin, Nannan Gao, Yong Peng, Zizhao Wu, Shuying Shen, Artur Grudtsin. Fine-grained leukocyte classification with deep residual learning for microscopic images. Computer Methods and Programs in Biomedicine, 162: 243-252, 2018.
[55] Feiwei Qin, Haibing Xia, Yong Peng, Zizhao Wu. Integrated modeling, simulation and visualization for nano materials. Complexity, Volume 2018 (2018), Article ID 5083247.
[56] Yong Peng, Bao-Liang Lu. Discriminative extreme learning machine with supervised sparsity preserving for image classification. Neurocomputing, 261: 242-252, 2017.
[57] Yong Peng, Wanzeng Kong, Bing Yang. Orthogonal extreme learning machine for image classification. Neurocomputing, 266: 458-464, 2017.
[58] Yong Peng, Bao-Liang Lu. Robust structured sparse representation via half-quadratic optimization for face recognition. Multimedia Tools and Applications,76(6): 8859-8880, 2017.
[59] Zhi-Jie Wang, Xiao Lin, Mei-E Fang, Bin Yao, Yong Peng, Haibin Guan, MinyiGuo. RE2L: An efficient output-sensitive algorithm for computing boolen operations on circular-arc polygons and its applications. Computer-Aided Design, 83(2):1–14, 2017.
[60] Yong Peng, Bao-Liang Lu. Discriminative manifold extreme learning machine and applications to image and EEG signal classification. Neurocomputing, 174:265–277, 2016.
[61] Yong Peng, Wei-Long Zheng, Bao-Liang Lu. An unsupervised discriminative extreme learning machine and its applications to data clustering. Neurocomputing, 174: 250–264, 2016.
[62] Xianzhong Long, Hongtao Lu, Yong Peng, Xianzhong Wang, Shaokun Feng. Image classification based on improved VLAD. Multimedia Tools and Applications,75(10), 5533–5555, 2016.
[63] Yong Peng, Suhang Wang, Xianzhong Long, Bao-Liang Lu. Discriminative graph regularized extreme learning machine and its application to face recognition. Neurocomputing,149: 340–353, 2015.（ESI高被引论文）
[64] Yong Peng, Bao-Liang Lu, Suhang Wang. Enhanced low rank representation via sparse manifold adaption for semi-supervised learning. Neural Networks, 65: 1–17, 2015.
[65] Yong Peng, Bao-Liang Lu. Hybrid learning clonal selection algorithm. Information Sciences, 296: 128–146, 2015.
[66] Yong Peng, Xianzhong Long, Bao-Liang Lu. Graph based semi-supervised learning via structure preserving low rank representation. Neural Processing Letters, 41(3): 389–406,2015.
[67] Xianzhong Long, Hongtao Lu, Yong Peng, Wenbin Li. Graph regularized discriminative nonnegative matrix factorization for face recognition. Multimedia Tools and Applications, 72(3): 2679–2699, 2014.
[68] Yong Peng, Bao-Liang Lu. A hierarchical particle swarm optimizer with latin sampling based memetic algorithm for numerical optimization. Applied Soft Computing, 13(5): 2823–2836, 2013.

中文权威/一级期刊论文列表：
[1] 李文政，王文娟，彭勇，孔万增。联合双映射域适应与图半监督标签估计的脑电情感识别方法。中国生物医学工程学报，42(5): 529-541, 2023.
[2] 秦飞巍，沈希乐，彭勇，邵艳利，袁文强，计忠平，白静。无人驾驶中的场景实时语义分割方法。计算机辅助设计与图形学学报，33 (7): 1026-1037, 2021.
[3] 林浒，彭勇。面向多目标优化的适应度共享免疫克隆算法。控制理论与应用，28（2）：206-214， 2011.