Publications

[C11] Chengxi Zhu, Yong Peng, Yinfeng Fang, and Wanzeng Kong. Label rectified and graph adaptive semi-supervised regression for electrode shifted gesture recognition. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, April 14-19, pages xxxx-xxxx, 2024.
[C10] Fangyao Shen, Zehao Zhang, Yong Peng, Hongjie Guo, Lina Chen, and Hong Gao. Self-supervised learning for sleep stage classification with temporal augmentation and false negative suppression. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, April 14-19, pages xxxx-xxxx, 2024.
[C9] Yuhang Ming, Jian Ma, Xingrui Yang, Weichen Dai, Yong Peng, and Wanzeng Kong. AEGIS-Net: Attention-guided Multi-Level Feature Aggregation for Indoor Place Recognition. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, April 14-19, pages xxxx-xxxx, 2024.
[J62] 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, DOI: 10.1109/TMM.2024.3358086, 2024.
[J61] Xing Li, Yikai Zhang, Yong Peng, and Wanzeng Kong. Enhanced performance of EEG-based brain-computer interfaces by joint sample and feature importance assessment. Health Information Science and Systems, DOI: 10.1007/s13755-024-00271-0, 2024.
[J60] Yifei Chen, Chenyan Zhang, Ben Chen, Yiyu Huang, Yifei Sun, Changmiao Wang, Feiwei Qin, Yong Peng, and 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, DOI: 10.1016/j.compbiomed.2024.107917, 2024.
[J59] Feiwei Qin, Kang Yan, Changmiao Wang, Ruiquan Ge, Yong Peng, and Kai Zhang. LKFormer: large kernel transformer for infrared image super-resolution. Multimedia Tools and Applications, DOI:10.1007/s11042-024-18409-3, 2024.
[J58] Keding Chen, Yong Peng, Feiping Nie, and Wanzeng Kong. Soft label guided unsupervised discriminative sparse subspace feature selection. Journal of Classification, DOI: 10.1007/s00357-024-09462-6, 2024.
[J57] Li Zhu, Youyang Liu, Riheng Liu, Yong Peng, Jianting Cao, 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.
[J56] 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.
[J55] 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, 400, Article ID 109978, 2023.
[J54] 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), Article ID 101661, 2023.
[J53] Yong Peng, Keding Chen, Feiping Nie, Bao-Liang Lu, and Wanzeng Kong. Two-dimensional embedded fuzzy data clustering. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(4):1263-1275, 2023.
[J52] 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), Article ID 101648, 2023.
[J51] 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, Article ID 109909, 2023.
[J50] Yong Peng, Honggang Liu, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, and Andrzej Cichocki. Joint EEG feature transfer and semi-supervised cross-subject emotion recognition. IEEE Transactions on Industrial Informatics, 19(7): 8104-8115, 2023.
[J49] 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.[Supplementray Material]
[J48] Jiajia Tang, Dongjun Liu, Xuanyu Jin, Yong Peng, Qibin Zhao, Yu Ding, and 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.
[J47] 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.
[J46] 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.
[J45] 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.
[CJ3] 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.
[J44] Yong Peng, Wenjuan Wang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, and 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.
[J43] Yong Peng, Fengzhe Jin, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, and 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.
[J42] Yong Peng, Yikai Zhang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, and Andrzej Cichocki. S3LRR: a unified model for joint discriminative subspace identification and semisupervised EEG emotion recognition. IEEE Transactions on Instrumentation and Measurement, 71, Article ID 2507313, 2022.
[J41] Yong Peng, Feiwei Qin, Wanzeng Kong, Yuan Ge, Feiping Nie, and 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 Highly Cited Paper in 2024)
[J40] Yikai Zhang, Ruiqi Guo, Yong Peng, Wanzeng Kong, Feiping Nie, and Bao-Liang Lu. An auto-weighting incremental random vector functional link network for EEG-based driving fatigue detection. IEEE Transactions on Instrumentation and Measurement, 71, Article ID: 4010014, 2022.
[J39] Xing Li, Fangyao Shen, Yong Peng, Wanzeng Kong, and 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.
[J38] Ruiqi Guo, Yong Peng, Wanzeng Kong, and 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): 10094–10108, 2022.
[J37] Bing Yang, Xueqin Xiang, Wanzeng Kong, Yong Peng, and Jinliang Yao. Adaptive multi-task learning using lagrange multiplier for automatic art analysis. Multimedia Tools and Applications, 81(3): 3715-3733, 2022.
[J36] Fangyao Shen, Yong Peng, Guojun Dai, Baoliang Lu, and Wanzeng Kong. Coupled projection transfer metric learning for cross-session emotion recognition from EEG. Systems, 10(2), Article ID: 47, 2022.
[J35] Wenzheng Li, and Yong Peng. Transfer EEG emotion recognition by combining semi-supervised regression with bipartite graph label propagation. Systems, 10(4), Article ID: 111, 2022.
[J34] Senwei Xu, Li Zhu, Wanzeng Kong, Yong Peng, Hua Hu, and 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.
[J33] Meie Fang, Zhuxin Jin, Feiwei Qin, Yong Peng, Chao Jiang, and Zhigeng Pan. Re-transfer learning and multi-modal learning assisted early diagnosis Alzheimer’s disease. Multimedia Tools and Applications, 81(20): 29159-29175, 2022.
[J32] Ziyuan Chen, Shuzhe Duan, and Yong Peng. EEG-based emotion recognition by retargeted semi-supervided regression with robust weights. Systems, 10(6), Article ID: 236, 2022.
[J31] Yong Peng, Wanzeng Kong, Feiwei Qin, Feiping Nie, Jinglong Fang, Bao-Liang Lu, and 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.
[J30] Yong Peng, Xin Zhu, Feiping Nie, Wanzeng Kong, and Yuan Ge. Fuzzy graph clustering. Information Sciences, 571: 38-49, 2021.
[J29] Yong Peng, Yikai Zhang, Feiwei Qin, and Wanzeng Kong. Joint non-negative and fuzzy coding with graph regularization for efficient data clustering. Egyptian Informatics Journal, 22(1): 91-100, 2021.
[J28] Xuanyu Jin, Jiajia Tang, Xianghao Kong, Yong Peng, Jianting Cao, Qibin Zhao, and 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.
[J27] Haowei Jiang, Feiwei Qin, Jin Cao, Yong Peng, and Yanli Shao. Recurrent Neural Network from Adder’s Perspective: Carry-lookahead RNN. Neural Networks, 144, 297-306, 2021.
[J26] Wenna Huang, Yong Peng, Yuan Ge, and Wanzeng Kong. A new kmeans formulation and its generalization achieved by joint spectral embedding and rotation. PeerJ Computer Science, 7, Article ID: e450, 2021.
[J25] Fangyao Shen, Yong Peng, Wanzeng Kong, and Guojun Dai. Multi-scale frequency bands ensemble learning for EEG-based emotion recognition. Sensors, 21(4), 1262, 2021.
[J24] Xinnan Lin, Feiwei Qin, Yong Peng, and Yanli Shao. Fine-Grained Pornographic Image Recognition with Multiple Feature Fusion Transfer Learning. International Journal of Machine Learning and Cybernetics, 12, 73-86, 2021.
[J23] Yikai Zhang, Yong Peng, Hongyu Bian, Yuan Ge, Feiwei Qin, and Wanzeng Kong. Auto-weighted concept factorization for joint feature map and data representation learning. Journal of Intelligent & Fuzzy Systems, 41(1): 69-81, 2021.
[J22] Yuxuan Zhu, Yong Peng, Yang Song, Kenji Ozawa, and 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.
[CJ2] 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.
[J21] Yong Peng, Qingxi Li, Wanzeng Kong, Feiwei Qin, Jianhai Zhang, and 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.
[J20] Yong Peng, Leijie Zhang, Wanzeng Kong, Feiwei Qin, and Jianhai Zhang. Joint low-rank representation and spectral regression for robust subspace learning. Knowledge-Based Systems, 195, 105723, 2020.
[J19] Yong Peng, Leijie Zhang, Wanzeng Kong, Feiwei Qin, and Jianhai Zhang. Low rank spectral regression via matrix factorization for efficient subspace learning. Journal of Intelligent & Fuzzy Systems, 39(3): 3401-3412, 2020.
[C8] Yong Peng, Qingxi Li, Wanzeng Kong, Jianhai Zhang, Bao-Liang Lu, and Andrzej Cichocki. Joint semi-supervised feature auto-weighting and classification model for EEG-based cross-subject sleep quality evaluation. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, May 4-8, pages 946-950, 2020.
[J18] Qinghao Ye, Daijian Tu, Feiwei Qin, Zizhao Wu, Yong Peng, and Shuying Shen. Dual attention based fine-grained leukocyte recognition for imbalanced microscopic images. Journal of Intelligent & Fuzzy Systems, 37(5): 6971-6982, 2019.
[C7] Yong Peng, Leijie Zhang, Wanzeng Kong, Feiping Nie, and Andrzej Cichocki. Joint structured graph learning and unsupervised feature selection. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 12-17, pages 3572-3576, 2019.
[C6] Yong Peng, Yanfang Long, Feiwei Qin, Wanzeng Kong, Feiping Nie, and Andrzej Cichocki. Flexible non-negative matrix factorization with adaptively learned graph regularization. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 12-17, pages 3107-3111, 2019.
[C5] Yong Peng, Rixin Tang, Wanzeng Kong, Jianhai Zhang, Feiping Nie, and Andrzej Cichocki. Joint structured graph learning and clustering via concept factorization. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 12-17, pages 3162-3166, 2019.
[J17] Yong Peng, Wanzeng Kong, Feiwei Qin, and Feiping Nie. Manifold adaptive kernelized low-rank representation for semi-supervised image classification. Complexity, Volume 2018 (2018), Article ID 2857594, 2018.
[J16] Feiwei Qin, Nannan Gao, Yong Peng, Zizhao Wu, Shuying Shen, and Artur Grudtsin. Fine-grained leukocyte classification with deep residual learning for microscopic images. Computer Methods and Programs in Biomedicine, 162: 243-252, 2018.
[J15] Feiwei Qin, Haibing Xia, Yong Peng, and Zizhao Wu. Integrated modeling, simulation and visualization for nano materials. Complexity, Volume 2018 (2018), Article ID 5083247.
[J14] Wanzeng Kong, Shijie Guo, Yanfang Long, Yong Peng, Hong Zeng, Xinyu Zhang, and Jianhai Zhang. Weighted extreme learning machine for P300 detection with application to brain computer interface. Journal of Ambient Intelligence and Humanized Computing, 10.1007/s12652-018-0840-1, May 2018.
[C4] Yong Peng, Rixin Tang, Wanzeng Kong, Feiwei Qin, and Feiping Nie. Parallel vector field regularized non-negative matrix factorization for image representation. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Canada, April 15-20, pages 2216-2220, 2018.
[C3] Jianhai Zhang, Shaokai Zhao, Guodong Yang, Jiajia Tang, Tao Zhang, Yong Peng, and Wanzeng Kong, Emotional-state brain network analysis revealed by minimum spanning tree using EEG signals. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Madrid, Spain, December 3-6, pages 1045-1048, 2018.
[C2] Jianhai Zhang, Na Zhang, Jiajia Tang, Jianting Cao, Wanzeng Kong, and Yong Peng. A new method for brain death diagnosis based on phase synchronization analysis with EEG. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Madrid, Spain, December 3-6, pages 1135-1138, 2018.
[J13] Yong Peng, and Bao-Liang Lu. Discriminative extreme learning machine with supervised sparsity preserving for image classification. Neurocomputing, 261: 242-252, 2017.
[J12] Yong Peng, Wanzeng Kong, and Bing Yang. Orthogonal extreme learning machine for image classification. Neurocomputing, 266: 458-464, 2017.
[J11] Yong Peng, and Bao-Liang Lu. Robust structured sparse representation via half-quadratic optimization for face recognition. Multimedia Tools and Applications,76(6): 8859-8880, 2017.
[J10] Zhi-Jie Wang, Xiao Lin, Mei-E Fang, Bin Yao, Yong Peng, Haibin Guan, and Minyi Guo. 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.
[J9] Yong Peng, and Bao-Liang Lu. Discriminative manifold extreme learning machine and applications to image and EEG signal classification. Neurocomputing, 174:265–277, 2016.
[J8] Yong Peng, Wei-Long Zheng, and Bao-Liang Lu. An unsupervised discriminative extreme learning machine and its applications to data clustering. Neurocomputing, 174: 250–264, 2016.
[J7] Xianzhong Long, Hongtao Lu, Yong Peng, Xianzhong Wang, and Shaokun Feng. Image classification based on improved VLAD. Multimedia Tools and Applications,75(10), 5533–5555, 2016.
[J6] Yong Peng, Suhang Wang, Xianzhong Long, and Bao-Liang Lu. Discriminative graph regularized extreme learning machine and its application to face recognition. Neurocomputing,149: 340–353, 2015. (ESI Highly Cited Paper in 2016)
[J5] Yong Peng, Bao-Liang Lu, and Suhang Wang. Enhanced low rank representation via sparse manifold adaption for semi-supervised learning. Neural Networks, 65: 1–17, 2015.
[J4] Yong Peng, and Bao-Liang Lu. Hybrid learning clonal selection algorithm. Information Sciences, 296: 128–146, 2015.
[J3] Yong Peng, Xianzhong Long, and Bao-Liang Lu. Graph based semi-supervised learning via structure preserving low rank representation. Neural Processing Letters, 41(3): 389–406,2015.
[J2] Xianzhong Long, Hongtao Lu, Yong Peng, and Wenbin Li. Graph regularized discriminative nonnegative matrix factorization for face recognition. Multimedia Tools and Applications, 72(3): 2679–2699, 2014.
[C1] Wei-Long Zheng, Jia-Yi Zhu, Yong Peng, and Bao-Liang Lu. EEG-based emotion classification using deep belief networks. IEEE International Conference on Multimedia and Expo (ICME), Chengdu, China, July 14-18, pages 1–6, 2014.
[J1] Yong Peng, and 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.
[CJ1] 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.