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Hot Papers and Important Contribution

Highly cited papers

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Recent Research Focus

1. Pattern Recognition and Biometrics

2. Image Processing And Video Analysis

3. Bioinformatics

4. Deep Learning

 

High Cited Papers:

C. Tian, Y. Xu, Z. Li, W. Zuo, L. Fei, H. Liu, Attention-guided CNN for Image Denoising, Neural Networks, 124: 117-129, 2020. (SCI).(paper)(code)(http)

C. Tian, Y. Xu, W. Zuo, Image Denoising Using Deep CNN with Batch Renormalization, Neural Networks, 121:461-473, 2020. (SCI).(paper)(code)(http)

J. Wen, X. Fang, J. Cui, L. Fei, K. Yan, Y. Chen, Y. Xu, Robust Sparse Linear Discriminant Analysis, IEEE Transactions on Circuits & Systems for Video Technology, 29(2):390-403, 2019(SCI)(paper)(code)(http)

J. Wen, Y. Xu, Z. Li, Z. Ma, Y. Xu, Inter-class sparsity based discriminative least square regression, Neural Networks,102:36-47, 2018 (SCI) (paper)(code)(http)

Z. Lai, W.K.Wong, Y. Xu, J. Yang. Approximate Orthogonal Sparse Embedding for Dimensionality Reduction, IEEE Transactions on Neural Networks and Learning Systems, 27(4),723-735,2016.(SCI)(paper)(code) (http)

Z. Zhang, Y. Xu, J. Yang, X. Li, D. Zhang, A Survey of Sparse Representation: Algorithms and Applications, IEEE Access,3, 490-530,2015(SCI) (paper) (code) (http) (The ideas, algorithms, and wide applications of sparse representation are comprehensively presented.)

Z. Lai, Y. Xu, Q. Chen, J. Yang, D. Zhang, Multilinear Sparse Principal Component Analysis,IEEE Transactions on Neural Networks and Learning Systems,25(10), 2014 (SCI)(paper) (code) (http)

Y. Xu, D. Zhang, J. Yang, J.-Y. Yang, A two-phase test sample sparse representation method for use with face recognition, IEEE Transactions on Circuits and Systems for Video Technology, 21(9), 1255-1262, 2011 (SCI) (paper) (code) (http)

 

Pattern Recognition And Biometrics:

J. Wen, K. Yan, Z. Zhang, Y. Xu, J. Wang, L. Fei, B. Zhang, Adaptive Graph Completion Based Incomplete Multi-view Clustering, IEEE Transactions on Multimedia, doi: 10.1109/TMM.2020.3013408. 2020(SCI). (paper) (code) (http)

J. Wen, Y. Xu, H. Liu, Incomplete Multi-view Spectral Clustering with Adaptive Graph Learning, IEEE Transactions on Cybernetics, 50(4):1418-1429, 2020. (SCI). (paper) (code) (http)

C. Liu, J. Wang, S. Duan, Y. Xu, Combining dissimilarity measures for image classification. Pattern Recognition Letters, 128(1):536-543, 2019. (SCI).(paper)(code)(http)

Y. Xu, Z. Li., C. Tian, J. Yang, Multiple vector representations of images and robust dictonary learning, Pattern Recognition Letters, 128:131-136, 2019. (SCI). (paper)(code)(http)

X. Luo , Y. Xu, J. Yang, Multi-resolution dictionary learning for face recognition, Pattern Recognition, 93: 283-292, 2019. (SCI) (paper) (code)(http)

H. Fan, F. Zhang, L. Xi, Z. Li, G. Liu, Y. Xu, LeukocyteMask: An automated localization and segmentation method for leukocyte in blood smear images using deep neural networks, Journal of BIOPHOTONICS, 12(7), 2019. (SCI) (paper) (code)(http)

Z. Zhang, L. Shao, Y. Xu, L. Liu, J. Yang, Marginal Representation Learning with Graph Structure Self-Adaptation,  IEEE Transactions on Neural Networks and Learning Systems, 29(10):4645-4659, 2018. (SCI) (paper) (code)(http)

J. Wen, X. Fang, Y. Xu, C. Tian, L. Fei, Low-rank representation with adaptive graph regularization. Neural Networks, 108:83-96, 2018. (SCI)(paper) (code)(http)

Z. Zhang, Y. Xu, L. Shao, J. Yang, Discriminative Block-Diagonal Representational Learning for Image Recognition, IEEE Transactions on Neural Networks and Learning systems,29(7):3111-3125, 2018. (SCI)(paper) (code)(http)

J.Wen, B. Zhang, Y. Xu, J. Yang, N. Han, Adaptive weighted nonnegative low-rank representation, Pattern Recognition, 81:326-340, 2018(SCI)(paper)(code)(http)

X. Fang , N. Han , J. Wu , Y. Xu, Approximate Low-Rank Projection Learning for Feature Extraction. IEEE Transactions on Neural Networks and Learning Systems, 29 (11):5228-5241,2018.(SCI)(paper(code)(http)

Y. Xu, Z. Li, J. Yang, D. Zhang, A Survey of Dictionary Learning Algorithms for Face Recognition, IEEE Access, 5:8502-8514, 2017(SCI)(paper)(code)(http)

Y. Xu, Z. Li, B. Zhang, J. Yang, J. You, Sample diversity, representation effectiveness and robust dictionary learning for face recognition, Information Sciences, 375:171-182, 2017. (SCI) (paper) (code) (http)

Z. Zhang, Z. Lai, Y. Xu, L. Shao, J. Wu, G. Xie, Discriminative Elastic-Net Regularized Linear Regression, IEEE Transactions on Image Processing, 26(3):1466-1481,2017. (SCI) (paper) (code) (http)

X. Fang, Y. Xu, Z. Lai, W. Wong, B. Fang, Regularized Label Relaxation Linear Regression, IEEE Transactions on Neural Networks and Learning Systems, 1-13, 2017. (SCI)(paper)(code)(http)

X. Fang, Y. Xu, X. Li, Z. Lai, S. Teng, L. Fei, Orthogonal self-guided similarity preserving projection for classification and clustering, Neural Networks, 88:1-8, 2017. (SCI) (paper)(code)(http)

Z. Li, Z. Lai, Y. Xu, J. Yang, D. Zhang. A Locality-Constrained and Label Embedding Dictionary Learning Algorithm for Image Classification, IEEE Transactions on Neural Networks and Learning Systems, 28(2), 278-293, 2017.(SCI) (paper)(code)(http)

L.Fei, Y. Xu, X. Fang, J. Yang, Low Rank Representation with Adaptive Distance Penalty for Semi-supervised Subspace Classification, Pattern Recognition, 67:252-262,2017. (SCI) (paper)(code)(http)

Y. Xu, Z. Zhong, J. Yang, J. You, D. Zhang. A New Discriminative Sparse Representation Method for Robust Face Recognition via l(2) Regularization, IEEE Transactions on Neural Networks and Learning Systems,28(10):2233 - 2242,2017 (SCI) (paper)(code)(http)

Y. Xu, Z. Zhang, G. Lu, J.Yang, Approximately Symmetrical Face Images for Image Preprocessing in Face Recognition and Sparse Representation Based Classification, Pattern Recognition, 54:68-82, 2016.(SCI) (paper) (code) (http)

X. Fang, Y. Xu, X. Li, Z. Lai, W.K. Wong, Robust Semi-Supervised Subspace Clustering via Non-Negative Low-Rank Representation, IEEE Transaction on Cybernetics, 46(8):1828-1838, 2016(SCI) (paper)(code) (http)

Z. Fan, Y. Xu, M. Ni, X. Fang, D. Zhang, Individualized Learning for Improving Kernel Fisher Discriminant Analysis, Pattern Recognition,58:100-109,2016(SCI) (paper) (code)(http)

L. Fei, Y. Xu, B. Zhang, X. Fang, J. Wen, Low-rank Representation Integrated With Principal Line Distance for Contactless Palmprint Recognition, Neurocomputing, 218(19):264-275,2016 (SCI)(paper)(code)(http)

Y. Xu, X. Fang,J. You, Y. Chen, H. Liu, Noise-free representation based classification and face recognition experiments. Neurocomputing , 147:307-314, 2015(paper) (code)

Y. Xu, X. Fang,J. Wu, X. Li, D. Zhang, Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation, IEEE Transactions on Image Processing, 25(2): 850-863, 2015 (SCI) (paper) (code) (http)

X. Fang, Y. Xu, X. Li, Z. Lai, W.K. Wong, Learning a Non-Negative Sparse Graph for Linear Regression, IEEE Transactions on Image Processing. 24(9):2760-2771,2015 (SCI) (paper) (code) (http)

Y. Xu, Y. Lu, Adaptive weighted fusion: A novel fusion approach for image classification. Neurocomputing, 168:566-574,2015 (SCI)(paper)(proof) (code) (http)

Y. Xu, B. Zhang, Z. Zhong, Multiple representations and sparse representation for image classification, Pattern Recognition Letters, 68:9-14,2015 (SCI) (paper) (code) (http)

Y. Xu, X. Li, J. Yang, Z. Lai, D. Zhang,Integrating conventional and inverse representation for face recognition, IEEE Transactions on Cybernetics, 44(10):1738-1746, 2014 (SCI) (paper) (code) (http) (idea and algorithm of inverse sparse representation are proposed)

Y. Xu, X. Fang, X. Li, J. Yang, J. You, H. Liu, S. Teng, Data uncertainty in face recognition, IEEE Transactions on Cybernetics, 44(10):1950-1961,2014(SCI)(paper)(code)(http) (Data uncertainty in face recognition is discussed and a novel sparse representation algorithm is proposed)

Z. Fan, Y. Xu, W. Zuo, J. Yang, J. Tang, Z. Lai, D. Zhang, Modified Principal Component Analysis: An Integration of Multiple Similarity Subspace Models. IEEE Transaction on Neural Network and Learning Systems, 25(8):1538-1552,2014 (SCI)(paper)(code)(http)

Z. Lai, Y. Xu, Z. Jin, D. Zhang, Human Gait Recognition via Sparse Discriminant Projection Learning, IEEE Transactions on Circuits and Systems for Video Technology,24(10):1651-1662,2014 (SCI)(paper) (code) (http)

X. Fang, Y. Xu, X. Li, Z. Fan, H. Liu, Y. Chen, Locality and similarity preserving embedding for feature selection, Neurocomputing, 128:304-315, 2014 (paper) (code)

Y. Xu, X. Li, J. Yang, D. Zhang,Integrate the original face image and its mirror image for face recognition, Neurocomputing, 131:191-199,2014 (SCI) (paper) (code)

Y. Xu, X. Zhu, Z. Li, G. Liu, Y. Lu, H. Liu, Using the original and ‘symmetrical face’ training samples to perform representation based two-step face recognition, Pattern Recognition, 46(4):1151-1158, 2013 (SCI) (paper) (code) (http)

Y. Xu, Q. Zhu, Z. Fan, D. Zhang, J. Mi, Z. Lai, Using the Idea of the Sparse Representation to Perform Coarse-to-Fine Face Recognition, Information Sciences, 238(20): 138-148, 2013 (SCI)(paper) (code) (http)

Y. Xu, Q. Zhu, Y. Chen, J.-S. Pan, An improvement to the nearest neighbor classifier and face recognition experiments, International Journal of Innovative Computing, Information and Control, 9(2):543-554, 2013 (paper) (code)

Y. Xu, Q. Zhu, A simple and fast representation-based face recognition method, Neural Computing and Applications,22(7-8): 1543-1549, 2013 (paper)(code)

Z. Lai, Y. Xu, J. Yang, J. Tang, D. Zhang, Sparse Tensor Discriminant Analysis, IEEE Transactions on Image Processing, 22(10):3904-3915, 2013 (SCI) (paper) (code)(http)

Y. Xu, Q. Zhu, Z. Fan, M. Qiu, Y. Chen, H. Liu, Coarse to fine K nearest neighbor classifier, Pattern Recognition Letters, 34(9): 980-986, 2013 (SCI) (paper) (code)

Y. Xu, Q. Zhu, Z. Fan, Y. Wang, J.-S. Pan, From the idea of ”sparse representation” to a representation-based transformation method for feature extraction, Neurocomputing,113:168-176,2013 (SCI) (paper) (code)

Y. Xu, Quaternion-Based Discriminant Analysis Method for Color Face Recognition, PLoS ONE, 7(8): e43493,2012(SCI) (paper) (code)(http)

Y. Xu, Z. Fan, Q. Zhu, Feature space-based human face image representation and recognition, Optical Engineering,51(1), 017205, 2012 (SCI)(paper) (code)

Y. Xu, A. Zhong, J.Yang, D. Zhang, Bimodal biometrics based on a representation and recognition approach, Optical Engineering, 50(3), 037202, 2011, (SCI) (paper) (code) (database)

Z. Fan, Y. Xu, D. Zhang, Local linear discriminant analysis framework using sample neighbors, IEEE Transactions on Neural Networks. 22(7):1119-1132, 2011 (SCI) (paper) (code) (http)

Y. Xu, D. Zhang, J. Yang, Z. Jin, J.-Y. Yang, Evaluate dissimilarity of samples in feature space for improving KPCA, International Journal of Information Technology & Decision Making, 10(3): 479-495, 2011 (SCI) (paper)(code)

Y. Xu, Q. Zhu, D. Zhang, Combine crossing matching scores with conventional matching scores for bimodal biometrics and face and palmprint recognition experiments, Neurocomputing, 74(18):3946-3952, 2011 (SCI) (paper) (code & dataset)

Y. Xu, A. Zhong, J. Yang, D. Zhang, LPP solution schemes for use with face recognition, Pattern Recognition, 43(12):4165-4176,2010(SCI) (paper) (code)

J. Wang, Y. Xu, D. Zhang, J. You, An efficient method for computing orthogonal discriminant vectors, Neurocomputing, 73(10-12):2168-2176,2010,(SCI) (paper) (code)

 

Deep Learning:

Tian C, Xu Y, Zuo W, Lin C, Zhang D. Asymmetric CNN for image super-resolution,IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021.(paper)(code)(http)

C. Tian, Y. Xu, W. Zuo, C. Lin, D. Zhang. Designing and Training of A Dual CNN for Image Denoising, Knowledge-Based Systems, 226:106949, 2021.(paper)(code)(http)

C. Tian, Y. Xu, W. Zuo, Image Denoising Using Deep CNN with Batch Renormalization, Neural Networks, 121:461-473, 2020. (SCI).(paper)(code)(http)

C. Tian, L. Fei, W. Zheng, Y. Xu, W. Zuo, C. Lin, Deep Learning on Image Denoising: An overview. Neural Networks, 131:251-275, 2020.(SCI)(paper)(http)

C. Tian, R. Zhu, Z. Wu, Y. Xu, W. Zuo, C. Chen, C. Lin. Lightweight image super-resolution with enhanced CNN, Knowledge-Based Systems, 205:106235, 2020. (SCI).(paper)(code)(http)

C. Tian, Y. Xu, W. Zuo, B. Zhang, L. Fei, C. Lin, Coarse-to-fine CNN for image super-resolution, IEEE Transactions on Multimedia, 23, 1489-1502, 2021.(SCI).(paper)(code)(http)

C. Tian, Y. Xu, Z. Li, W. Zuo, L. Fei, H. Liu, Attention-guided CNN for Image Denoising, Neural Networks, 124: 117-129, 2020. (SCI).(paper)(code)(http)

C. Tian, Y. Xu, L. Fei, J. Wang, J. Wen, N. Luo, Enhanced CNN for image denoising,CAAI Transaction on Intelligent Technology, 4(1):17– 23, 2019. (paper)(code)(http).

吴帅. 徐勇.赵东宁. 基于深度卷积网络的目标检测综述,模式识别与人工智能, 31(4):335-346, 2018. (paper)(http)

C. Tian, Y. Xu, L. Fei, K. Yan, Deep Learning for Image Denoising: A Survey, The 12th International Conference on Genetic and Evolutionary Computing (ICGEC 2018): 563-572, 2018. (paper)(http)

K. Guo, S. Wu, Y. Xu, Face recognition using both visible light image and near-infrared image and a deep network, CAAI Transactions on Intelligence Technology, 2(1): 39-47, 2017(paper)(code)(http)

吕梦思.徐勇. 基于深度学习的实时行人检测方案.(文档)(code)

何建霆. 徐勇.2017cccv遥感目标提取挑战赛解决方案.(文档)(code)

 

Bioinformatics and Medical Image Analysis:

C. Feng, Z. Yang, H. Fu, Y. Xu, J. Yang, L. Shao, DONet: Dual-Octave Network for Fast MR Image Reconstruction, IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2021.3090303, 2021.(paper)(code)(http)

C. Feng, K. Wang, S. Lu, Y. Xu, X. Li, Brain MRI super-resolution using coupled-projection residual network, Neurocomputing, 456:190-199, 2021.(paper)(code)(http)


K Yan, X Fang, Y Xu, B Liu, Protein Fold Recognition based on Multi-view Modeling, Bioinformatics, 35(17):2982-2990, 2019.(paper)(code)(http)

J.-X. Liu, D. Wang,Y.-L. Gao, C.-H. Zheng, Y. Xu, J. Yu, Regularized Non-negative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Samples: a Survey,  IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15(3): 974-987, 2018. (SCI) (paper)(code)(http)

K. Yan , Y. Xu , X. Fang, C. Zheng, B. Liu, Protein fold recognition based on sparse representation based classification. Artificial intelligence in medicine, 79: 1-8,2017.(SCI)(paper)(code)(http)

J-X. Liu, Y. Xu, C.-H. Zheng, Y. Wang, J.-Y. Yang, Characteristic Gene Selection via Weighting Principal Components by Singular Values, PLoS ONE, 7(7): e38873 (SCI) (paper) (code)

 

Video Analysis:

Z. Zhong, B. Zhang, G. Lu, Y. Zhao, and Y. Xu, An Adaptive Background Modeling Method for Foreground Segmentation, IEEE Transactions on Intelligent Transportation Systems, 18(5):1109-1121,2017 (SCI). (paper)(code)(http)

Y. Xu, J. Dong, B. Zhang, D. Xu, Background Modeling Methods in Video Analysis: A review and comparative evaluation, CAAI Transactions on Intelligence Technology, 1(1): 43-60,2016 (paper)(code)(http)

Y. Xu, J. Wen, L. Fei, Z. Zhang, Review of video and image defogging algorithms and related studies on image restoration and enhancement, IEEE Access, 4: 165-188, 2016 (SCI) (paper) (code) (http)

J. Wen, Y. Xu, J. Tang, Y. Zhan, Z. Lai, X. Guo, Joint video frame set division and low-rank decomposition for background subtraction, IEEE Transactions on Circuits and Systems for Video Technology, 24(12):2034-2048, 2014 (SCI)(paper) (database) (http)

 

C. Feng, H. Fu, S. Yuan, Y. Xu, Multi-Contrast MRI Super-Resolution via a Multi-Stage Integration Network, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.(paper)(code)(http)

C. Feng, Y. Yan, H. Fu, L. Chen, Y. Xu, Task Transformer Network for Joint MRI Reconstruction and Super-Resolution, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.(paper)(code)(http)

C. Feng, Z. Yang, G. Chen, Y. Xu, L. Shao, Dual-Octave Convolution for Accelerated Parallel MR Image Reconstruction, The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), 2021.(paper)(code)(http)

J. Wen, Z. Zhang, Y. Xu, B. Zhang, L. Fei, H. Liu. Unified Embedding Alignment with Missing Views Inferring for Incomplete Multi-View Clustering, The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019). (paper)(code)(Accepted)

J. Wen, Z. Zhang, Y. Xu, Z. Zhong, Incomplete Multi-view Clustering via Graph Regularized Matrix Factorization, Proceedings of the European Conference on Computer Vision Workshops. Springer, Cham, 2018: 593-608. (paper)(code)(http).

L. Fei, Y. Xu, S. Teng, W. Zhang, W. Tang, X. Fang, Local Orientation Binary Pattern with Use for Palmprint Recognition, 12th Chinese Conference on Biometric Recogniton (CCBR) 2017(paper)(code)(http). (Best Paper)

 
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