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HPPLO-Net: Unsupervised LiDAR Odometry Using a Hierarchical Point-to-Plane Solver Journal article
Zhou,Beibei, Tu,Yiming, Jin,Zhong, Xu,Chengzhong, Kong,Hui. HPPLO-Net: Unsupervised LiDAR Odometry Using a Hierarchical Point-to-Plane Solver[J]. IEEE Transactions on Intelligent Vehicles, 2023, 9(1), 2727-2739.
Authors:  Zhou,Beibei;  Tu,Yiming;  Jin,Zhong;  Xu,Chengzhong;  Kong,Hui
Favorite | TC[WOS]:3 TC[Scopus]:3  IF:14.0/11.2 | Submit date：2023/08/03
Costs  Feature Extraction  Hierarchical Framework  Laser Radar  Lidar Odometry  Msa Layer  Odometry  Optimization  Point Cloud Compression  Scene Flow  Three-dimensional Displays  Weighted Point-to-plane Svd  
Partial Discharge Detection Method Based on DD-DT CWT and Singular Value Decomposition Journal article
Wu, Chao, Gao, Yiran, Wang, Ruoyan, Wang, Kai, Liu, Siyang, Nie, Yongjie, Wang, Ping. Partial Discharge Detection Method Based on DD-DT CWT and Singular Value Decomposition[J]. Journal of Electrical Engineering and Technology, 2022, 17(4), 2433 - 2439.
Authors:  Wu, Chao;  Gao, Yiran;  Wang, Ruoyan;  Wang, Kai;  Liu, Siyang; et al.
Favorite | TC[WOS]:2 TC[Scopus]:2  IF:1.6/1.4 | Submit date：2022/05/17
Double-density Dual-tree Complex Wavelet Transform (Dd-dt Cwt)  Partial Discharge (Pd)  Singular Value Decomposition (Svd)  
Fast and Robust Dictionary-based Classification for Image Data Journal article
Zeng, S., Zhang, B., Gou, J., Xu, Y., Huang, W.. Fast and Robust Dictionary-based Classification for Image Data[J]. ACM Transactions on Knowledge Discovery from Data (TKDD), 2021, 15(6), 97.
Authors:  Zeng, S.;  Zhang, B.;  Gou, J.;  Xu, Y.;  Huang, W.
Favorite | TC[WOS]:7 TC[Scopus]:7  IF:4.0/3.9 | Submit date：2022/07/13
Image Classification  Regularization  Sparse Representation  Dictionary Learning  Svd  
Prior Knowledge Regularized Multiview Self-Representation and its Applications Journal article
Xiao, Xiaolin, Chen, Yongyong, Gong, Yue Jiao, Zhou, Yicong. Prior Knowledge Regularized Multiview Self-Representation and its Applications[J]. IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(3), 1325-1338.
Authors:  Xiao, Xiaolin;  Chen, Yongyong;  Gong, Yue Jiao;  Zhou, Yicong
Favorite | TC[WOS]:27 TC[Scopus]:28  IF:10.2/10.4 | Submit date：2021/12/07
Low-rank Tensor Representation  Multiview  Prior Knowledge  Self-representation  Semisupervised Classification  Tensor Singular Value Decomposition (T-svd)  Weakly Supervised Clustering  
Common Spatial Pattern Reformulated for Regularizations in Brain-Computer Interfaces Journal article
Wang, Boyu, Wong, Chi Man, Kang, Zhao, Liu, Feng, Shui, Changjian, Wan, Feng, Chen, C. L.Philip. Common Spatial Pattern Reformulated for Regularizations in Brain-Computer Interfaces[J]. IEEE Transactions on Cybernetics, 2020, 51(10), 5008-5020.
Authors:  Wang, Boyu;  Wong, Chi Man;  Kang, Zhao;  Liu, Feng;  Shui, Changjian; et al.
Favorite | TC[WOS]:38 TC[Scopus]:36  IF:9.4/10.3 | Submit date：2021/12/08
Brain-computer Interface (Bci)  Common Spatial Pattern (Csp)  Generalized Eigenvalue Problem (Gep)  Least Squares  Multitask Learning  Singular Value Decomposition (Svd)  Sparse Learning  Transfer Learning  
Locating splicing forgery by adaptive-SVD noise estimation and vicinity noise descriptor Journal article
Liu,Bo, Pun,Chi Man. Locating splicing forgery by adaptive-SVD noise estimation and vicinity noise descriptor[J]. NEUROCOMPUTING, 2020, 387, 172-187.
Authors:  Liu,Bo;  Pun,Chi Man
Favorite | TC[WOS]:15 TC[Scopus]:18  IF:5.5/5.5 | Submit date：2021/03/11
Noise Estimation  Adaptive Svd  Splicing Forgery  Image Forensics  
An Effective Sparse Representation Approach for Wireless Channels Based on the Modified Takenaka-Malmquist Basis Conference paper
Qiangrong Xu, Yong Fang, Liming Zhang. An Effective Sparse Representation Approach for Wireless Channels Based on the Modified Takenaka-Malmquist Basis[C]:IEEE, 2019, 273-277.
Authors:  Qiangrong Xu;  Yong Fang;  Liming Zhang
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2022/05/17
K-svd  Public Modified Takenaka Malmquist Basis  Sparse Representation  Wireless Channels  
A Weighted K-SVD-Based Double Sparse Representations Approach for Wireless Channels Using the Modified Takenaka-Malmquist Basis Journal article
Lei Y., Fang Y., Zhang L.. A Weighted K-SVD-Based Double Sparse Representations Approach for Wireless Channels Using the Modified Takenaka-Malmquist Basis[J]. IEEE Access, 2018, 6, 54331-54342.
Authors:  Lei Y.;  Fang Y.;  Zhang L.
Favorite | TC[WOS]:4 TC[Scopus]:4 | Submit date：2019/04/04
Parallel Update  Public Weighted Modified Takenaka-malmquist Basis  Sparse Representations  Training Method  Weighted K-svd  Wireless Channels  
Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture Journal article
Chen, C. L. Philip, Liu, Zhulin. Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29(1), 10-24.
Authors:  Chen, C. L. Philip;  Liu, Zhulin
Favorite | TC[WOS]:979 TC[Scopus]:1405  IF:10.2/10.4 | Submit date：2018/10/30
Big Data  Big Data Modeling  Broad Learning System (Bls)  Deep Learning  Incremental Learning  Random Vector Functional-link Neural Networks (Rvflnn)  Single Layer Feedforward Neural Networks (Slfn)  Singular Value Decomposition (Svd)  
Broad learning system: Feature extraction based on K-means clustering algorithm Conference paper
Liu Z., Zhou J., Chen C.L.P.. Broad learning system: Feature extraction based on K-means clustering algorithm[C], 2017, 683-687.
Authors:  Liu Z.;  Zhou J.;  Chen C.L.P.
Favorite | TC[WOS]:31 TC[Scopus]:44 | Submit date：2019/02/11
Broad Learning System  Deep Learning  Feature Representation  Incremental Learning  K-means  Random Vector Functional Link Networks  Single Layer Feedforward Neural Networks  Svd