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2020 – today
- 2025
[j66]Tianxiang Wang
, Qun Dai:
A self-supervised semi-supervised echocardiographic video left ventricle segmentation method. Biomed. Signal Process. Control. 101: 107211 (2025)- [j65]Kanglin Qu, Pan Gao, Qun Dai, Yuanhao Sun, Xu Hua:
Attribute reduction using self-information uncertainty measures in optimistic neighborhood extreme-granulation rough set. Inf. Sci. 686: 121340 (2025) - 2024
- [j64]Huihui Yu, Qun Dai:
Self-supervised multi-task learning for medical image analysis. Pattern Recognit. 150: 110327 (2024) - [j63]Tianxiang Wang, Qun Dai:
A patch distribution-based active learning method for multiple instance Alzheimer's disease diagnosis. Pattern Recognit. 150: 110341 (2024) - [j62]Wenjuan Tang, Qun Dai, Fan Hao:
An Efficient Knowledge Distillation-Based Detection Method for Infrared Small Targets. Remote. Sens. 16(17): 3173 (2024) - [j61]Wenjuan Tang, Qun Dai, Fan Hao:
Differential Attention Orientated Cascade Network for Infrared Small Target Detection. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 9253-9265 (2024) - [c4]Yao Yuan, Wutao Liu, Pan Gao, Qun Dai, Jie Qin:
Unified Unsupervised Salient Object Detection via Knowledge Transfer. IJCAI 2024: 1616-1624 - [i2]Yao Yuan, Wutao Liu, Pan Gao, Qun Dai, Jie Qin:
Unified Unsupervised Salient Object Detection via Knowledge Transfer. CoRR abs/2404.14759 (2024) - [i1]Qun Dai, Chunyang Yuan, Yimian Dai, Yuxuan Li, Xiang Li, Kang Ni, Jianhui Xu, Xiangbo Shu, Jian Yang:
GrokLST: Towards High-Resolution Benchmark and Toolkit for Land Surface Temperature Downscaling. CoRR abs/2409.19835 (2024) - 2023
- [j60]Tianxiang Wang, Qun Dai:
SURVS: A Swin-Unet and game theory-based unsupervised segmentation method for retinal vessel. Comput. Biol. Medicine 166: 107542 (2023) - [j59]Tianxiang Wang, Qun Dai, Muxuan Yuan:
Deep Pixel Restoration Loop Coding Network [Application Notes] [Application Notes]. IEEE Comput. Intell. Mag. 18(2): 94-103 (2023) - [j58]Xin Shen, Qun Dai, Gangliang Zhu, Jing Zhang:
Dynamic ensemble pruning algorithms fusing meta-learning with heuristic parameter optimization for time series prediction. Expert Syst. Appl. 225: 120148 (2023) - [j57]Qiheng Wei, Qun Dai:
Adversarial unsupervised domain adaptation based on generative adversarial network for stock trend forecasting. Intell. Data Anal. 27(5): 1477-1502 (2023) - [j56]HuiHui Yu, Qun Dai:
AE-DIL: A double incremental learning algorithm for non-stationary time series prediction via adaptive ensemble. Inf. Sci. 636: 118916 (2023) - [j55]Xin Shen, Qun Dai, Wusat Ullah:
An active learning-based incremental deep-broad learning algorithm for unbalanced time series prediction. Inf. Sci. 642: 119103 (2023) - [j54]Jing Zhang, Qun Dai:
MrCAN: Multi-relations aware convolutional attention network for multivariate time series forecasting. Inf. Sci. 643: 119277 (2023) - [c3]Jia Xu, Wanjie Tao, Zulong Chen, Jin Huang, Huihui Liu, Hong Wen, Shenghua Ni, Qun Dai, Yu Gu:
PlanRanker: Towards Personalized Ranking of Train Transfer Plans. KDD 2023: 5315-5326 - [c2]Wanjie Tao, Huihui Liu, Xuqi Li, Qun Dai, Hong Wen, Zulong Chen:
Event-Aware Adaptive Clustering Uplift Network for Insurance Creative Ranking. SIGIR 2023: 1966-1970 - 2022
- [j53]HuiHui Yu, Qun Dai:
DWE-IL: a new incremental learning algorithm for non-stationary time series prediction via dynamically weighting ensemble learning. Appl. Intell. 52(1): 174-194 (2022) - [j52]Muxuan Yuan, Qun Dai:
A novel deep pixel restoration video prediction algorithm integrating attention mechanism. Appl. Intell. 52(5): 5015-5033 (2022) - [j51]Chenrui Yin, Qun Dai:
A deep multivariate time series multistep forecasting network. Appl. Intell. 52(8): 8956-8974 (2022) - [j50]Han Lu, Qun Dai:
A self-supervised COVID-19 CT recognition system with multiple regularizations. Comput. Biol. Medicine 150: 106149 (2022) - [j49]Rui Ye, Qun Dai:
A relationship-aligned transfer learning algorithm for time series forecasting. Inf. Sci. 593: 17-34 (2022) - [j48]Lin Guo, Qun Dai:
End-to-end variational graph clustering with local structural preservation. Neural Comput. Appl. 34(5): 3767-3782 (2022) - [j47]Jing Zhang, Qun Dai:
A cost-sensitive active learning algorithm: toward imbalanced time series forecasting. Neural Comput. Appl. 34(9): 6953-6972 (2022) - [j46]Jing Zhang, Qun Dai:
Latent adversarial regularized autoencoder for high-dimensional probabilistic time series prediction. Neural Networks 155: 383-397 (2022) - [j45]Lin Guo, Qun Dai:
Graph Clustering via Variational Graph Embedding. Pattern Recognit. 122: 108334 (2022) - 2021
- [j44]Gangliang Zhu, Qun Dai:
EnsPKDE&IncLKDE: a hybrid time series prediction algorithm integrating dynamic ensemble pruning, incremental learning, and kernel density estimation. Appl. Intell. 51(2): 617-645 (2021) - [j43]Qitao Gu, Qun Dai:
A novel active multi-source transfer learning algorithm for time series forecasting. Appl. Intell. 51(3): 1326-1350 (2021) - [j42]Qitao Gu, Qun Dai, HuiHui Yu, Rui Ye:
Integrating Multi-Source Transfer Learning, Active Learning and Metric Learning paradigms for Time Series Prediction. Appl. Soft Comput. 109: 107583 (2021) - [j41]Lin Guo, Qun Dai:
Laplacian regularized low-rank sparse representation transfer learning. Int. J. Mach. Learn. Cybern. 12(3): 807-821 (2021) - [j40]Jing Zhang, Qun Dai, ChangSheng Yao:
DEP-TSPmeta: a multiple criteria Dynamic Ensemble Pruning technique ad-hoc for time series prediction. Int. J. Mach. Learn. Cybern. 12(8): 2213-2236 (2021) - [j39]Rui Ye, Qun Dai:
Implementing transfer learning across different datasets for time series forecasting. Pattern Recognit. 109: 107617 (2021) - 2020
- [j38]Gang Song, Qun Dai, Xiaomeng Han, Lin Guo:
Two novel ELM-based stacking deep models focused on image recognition. Appl. Intell. 50(5): 1345-1366 (2020) - [j37]Chunyang Zhang, Qun Dai, Gang Song:
DeepCascade-WR: a cascading deep architecture based on weak results for time series prediction. Int. J. Mach. Learn. Cybern. 11(4): 825-840 (2020)
2010 – 2019
- 2019
- [j36]Jinhua Li, Qun Dai:
A new dual weights optimization incremental learning algorithm for time series forecasting. Appl. Intell. 49(10): 3668-3693 (2019) - [j35]Rui Ye, Qun Dai:
MultiTL-KELM: A multi-task learning algorithm for multi-step-ahead time series prediction. Appl. Soft Comput. 79: 227-253 (2019) - [j34]Qun Dai, Lin Guo:
Two novel hybrid Self-Organizing Map based emotional learning algorithms. Neural Comput. Appl. 31(7): 2921-2938 (2019) - [j33]Jinhua Li, Qun Dai, Rui Ye:
A novel double incremental learning algorithm for time series prediction. Neural Comput. Appl. 31(10): 6055-6077 (2019) - [j32]ChangSheng Yao, Qun Dai, Gang Song:
Several Novel Dynamic Ensemble Selection Algorithms for Time Series Prediction. Neural Process. Lett. 50(2): 1789-1829 (2019) - [j31]Rui Ye, Qun Dai, Meiling Li:
A hybrid transfer learning algorithm incorporating TrSVM with GASEN. Pattern Recognit. 92: 192-202 (2019) - 2018
- [j30]Xiaomeng Han, Qun Dai:
Batch-normalized Mlpconv-wise supervised pre-training network in network. Appl. Intell. 48(1): 142-155 (2018) - [j29]Meiling Li, Qun Dai:
A novel knowledge-leverage-based transfer learning algorithm. Appl. Intell. 48(8): 2355-2372 (2018) - [j28]Rui Ye, Qun Dai:
A novel transfer learning framework for time series forecasting. Knowl. Based Syst. 156: 74-99 (2018) - [j27]Rui Ye, Qun Dai:
A Novel Greedy Randomized Dynamic Ensemble Selection Algorithm. Neural Process. Lett. 47(2): 565-599 (2018) - 2017
- [j26]Qun Dai, ChangSheng Yao:
A hierarchical and parallel branch-and-bound ensemble selection algorithm. Appl. Intell. 46(1): 45-61 (2017) - [j25]Qun Dai, Rui Ye, Zhuan Liu:
Considering diversity and accuracy simultaneously for ensemble pruning. Appl. Soft Comput. 58: 75-91 (2017) - [j24]Gang Song, Qun Dai:
A novel double deep ELMs ensemble system for time series forecasting. Knowl. Based Syst. 134: 31-49 (2017) - 2016
- [j23]Ting Zhang, Qun Dai:
Hybrid ensemble selection algorithm incorporating GRASP with path relinking. Appl. Intell. 44(3): 704-724 (2016) - [j22]Qun Dai, Xiaomeng Han:
An efficient ordering-based ensemble pruning algorithm via dynamic programming. Appl. Intell. 44(4): 816-830 (2016) - [j21]Changjia Wang, Qun Dai:
Local well-posedness for Boussinesq approximation with shear dependent viscosities in 3D. Comput. Math. Appl. 72(1): 131-146 (2016) - [j20]Qun Dai, Gang Song:
A novel Supervised Competitive Learning algorithm. Neurocomputing 191: 356-362 (2016) - [j19]Zhongchen Ma, Qun Dai:
Selected an Stacking ELMs for Time Series Prediction. Neural Process. Lett. 44(3): 831-856 (2016) - 2015
- [j18]Qun Dai, Meiling Li:
Introducing randomness into greedy ensemble pruning algorithms. Appl. Intell. 42(3): 406-429 (2015) - [j17]Ting Zhang, Qun Dai, Zhongchen Ma:
Extreme learning machines' ensemble selection with GRASP. Appl. Intell. 43(2): 439-459 (2015) - [j16]Qun Dai, Ting Zhang, Ningzhong Liu:
A new reverse reduce-error ensemble pruning algorithm. Appl. Soft Comput. 28: 237-249 (2015) - [j15]Zhongchen Ma, Qun Dai, Ningzhong Liu:
Several novel evaluation measures for rank-based ensemble pruning with applications to time series prediction. Expert Syst. Appl. 42(1): 280-292 (2015) - 2014
- [j14]Zhuan Liu, Qun Dai, Ningzhong Liu:
Ensemble selection by GRASP. Appl. Intell. 41(1): 128-144 (2014) - [j13]Qun Dai, Zhongchen Ma, Qiongyu Xie:
A two-phased and Ensemble scheme integrated Backpropagation algorithm. Appl. Soft Comput. 24: 1124-1135 (2014) - 2013
- [j12]Qun Dai:
Back-propagation with diversive curiosity: An automatic conversion from search stagnation to exploration. Appl. Soft Comput. 13(1): 483-495 (2013) - [j11]Qun Dai, Zhuan Liu:
ModEnPBT: A Modified Backtracking Ensemble Pruning algorithm. Appl. Soft Comput. 13(11): 4292-4302 (2013) - [j10]Qun Dai:
A novel ensemble pruning algorithm based on randomized greedy selective strategy and ballot. Neurocomputing 122: 258-265 (2013) - [j9]Qun Dai:
A competitive ensemble pruning approach based on cross-validation technique. Knowl. Based Syst. 37: 394-414 (2013) - [j8]Qun Dai:
An efficient ensemble pruning algorithm using One-Path and Two-Trips searching approach. Knowl. Based Syst. 51: 85-92 (2013) - [c1]Qun Dai, Marc Aurel Schnabel:
Relationship between Mean Radiant Temperature and Building Type for Pedestrians in Rotterdam. CAAD Futures 2013: 306-314 - 2012
- [j7]Qun Dai, Ningzhong Liu:
Alleviating the problem of local minima in Backpropagation through competitive learning. Neurocomputing 94: 152-158 (2012) - 2011
- [j6]Qun Dai, Ningzhong Liu:
The build of n-Bits Binary Coding ICBP Ensemble System. Neurocomputing 74(17): 3509-3519 (2011) - 2010
- [j5]Qun Dai:
The build of a dynamic classifier selection ICBP system and its application to pattern recognition. Neural Comput. Appl. 19(1): 123-137 (2010)
2000 – 2009
- 2006
- [j4]Qun Dai, Songcan Chen:
Integrating the improved CBP model with kernel SOM. Neurocomputing 69(16-18): 2208-2216 (2006) - 2005
- [j3]Songcan Chen, Qun Dai:
Discounted least squares-improved circular back-propogation neural networks with applications in time series prediction. Neural Comput. Appl. 14(3): 250-255 (2005) - [j2]Qun Dai, Songcan Chen:
Chained DLS-ICBP Neural Networks with Multiple Steps Time Series Prediction. Neural Process. Lett. 21(2): 95-107 (2005) - 2003
- [j1]Qun Dai, Songcan Chen, Benzhu Zhang:
Improved CBP Neural Network Model with Applications in Time Series Prediction. Neural Process. Lett. 18(3): 217-231 (2003)
Coauthor Index
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