| Using the idea of the sparse representation to perform coarse-to-fine face recognition Y Xu, Q Zhu, Z Fan, D Zhang, J Mi, Z Lai Information sciences 238, 138-148, 2013 | 167 | 2013 |
| A new constrained independent component analysis method DS Huang, JX Mi IEEE transactions on neural networks 18 (5), 1532-1535, 2007 | 139 | 2007 |
| Review study of interpretation methods for future interpretable machine learning JX Mi, AD Li, LF Zhou IEEE Access 8, 191969-191985, 2020 | 77 | 2020 |
| The nearest-farthest subspace classification for face recognition JX Mi, DS Huang, B Wang, X Zhu Neurocomputing 113, 241-250, 2013 | 66 | 2013 |
| Robust PCA based method for discovering differentially expressed genes JX Liu, YT Wang, CH Zheng, W Sha, JX Mi, Y Xu BMC bioinformatics 14, 1-10, 2013 | 66 | 2013 |
| Comparison of Gating Properties and Use-Dependent Block of Nav1.5 and Nav1.7 Channels by Anti-Arrhythmics Mexiletine and Lidocaine Y Wang, J Mi, K Lu, Y Lu, KW Wang PLoS One 10 (6), e0128653, 2015 | 59 | 2015 |
| Principal component analysis based on nuclear norm minimization JX Mi, YN Zhang, Z Lai, W Li, L Zhou, F Zhong Neural Networks 118, 1-16, 2019 | 47 | 2019 |
| Face recognition using sparse representation-based classification on k-nearest subspace JX Mi, JX Liu PloS one 8 (3), e59430, 2013 | 38 | 2013 |
| Pose-robust face recognition with Huffman-LBP enhanced by Divide-and-Rule strategy LF Zhou, YW Du, WS Li, JX Mi, X Luan Pattern Recognition 78, 43-55, 2018 | 31 | 2018 |
| Robust face recognition via sparse boosting representation T Liu, JX Mi, Y Liu, C Li Neurocomputing 214, 944-957, 2016 | 31 | 2016 |
| A novel algorithm for independent component analysis with reference and methods for its applications JX Mi PloS one 9 (5), e93984, 2014 | 30 | 2014 |
| A novel method for recognizing face with partial occlusion via sparse representation JX Mi, D Lei, J Gui Optik 124 (24), 6786-6789, 2013 | 27 | 2013 |
| Image compression using principal component neural network J Mi, DS Huang ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004. 1 …, 2004 | 21 | 2004 |
| Adaptive class preserving representation for image classification JX Mi, Q Fu, W Li Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 18 | 2017 |
| A comparative study and improvement of two ICA using reference signal methods JX Mi, Y Xu Neurocomputing 137, 157-164, 2014 | 16 | 2014 |
| Robust supervised sparse representation for face recognition JX Mi, Y Sun, J Lu, H Kong Cognitive Systems Research 62, 10-22, 2020 | 13 | 2020 |
| New robust face recognition methods based on linear regression JX Mi, JX Liu, J Wen Public Library of Science 7 (8), e42461, 2012 | 13 | 2012 |
| Multi‐step linear representation‐based classification for face recognition JX Mi, T Liu IET Computer Vision 10 (8), 836-841, 2016 | 12 | 2016 |
| Designing efficient convolutional neural network structure: A survey JX Mi, J Feng, KY Huang Neurocomputing 489, 139-156, 2022 | 11 | 2022 |
| Principal component analysis based on block-norm minimization JX Mi, Q Zhu, J Lu Applied Intelligence 49, 2169-2177, 2019 | 11 | 2019 |
Yong XuBio-Computing Research Center, Harbin Institute of Technology, ShenzhenVerified email at hitsz.edu.cn
