| 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 |
| Coarse to fine K nearest neighbor classifier Y Xu, Q Zhu, Z Fan, M Qiu, Y Chen, H Liu Pattern recognition letters 34 (9), 980-986, 2013 | 160 | 2013 |
| Weighted sparse representation for face recognition Z Fan, M Ni, Q Zhu, E Liu Neurocomputing 151, 304-309, 2015 | 98 | 2015 |
| An improvement to the nearest neighbor classifier and face recognition experiments Y Xu, Q Zhu, Y Chen, JS Pan Int. J. Innov. Comput. Inf. Control 9 (2), 543-554, 2013 | 86 | 2013 |
| Abnormal crowd behavior detection by using the particle entropy X Gu, J Cui, Q Zhu Optik 125 (14), 3428-3433, 2014 | 82 | 2014 |
| A simple and fast representation-based face recognition method Y Xu, Q Zhu Neural Computing & Applications, 1-7, 2012 | 75 | 2012 |
| Feature space-based human face image representation and recognition Y Xu, Z Fan, Q Zhu Optical Engineering 51, 017205, 2012 | 61 | 2012 |
| Combine crossing matching scores with conventional matching scores for bimodal biometrics and face and palmprint recognition experiments Y Xu, Q Zhu, D Zhang Neurocomputing 74 (18), 3946-3952, 2011 | 58 | 2011 |
| Pose-invariant face recognition using facial landmarks and Weber local descriptor Z Zhang, L Wang, Q Zhu, SK Chen, Y Chen Knowledge-Based Systems 84, 78-88, 2015 | 54 | 2015 |
| A novel speech enhancement method based on constrained low-rank and sparse matrix decomposition C Sun, Q Zhu, M Wan Speech Communication 60, 44-55, 2014 | 52 | 2014 |
| Multi-directional two-dimensional PCA with matching score level fusion for face recognition Q Zhu, Y Xu Neural Computing & Applications, 1-6, 2012 | 51 | 2012 |
| Recent advances of deep learning for computational histopathology: principles and applications Y Wu, M Cheng, S Huang, Z Pei, Y Zuo, J Liu, K Yang, Q Zhu, J Zhang, ... Cancers 14 (5), 1199, 2022 | 49 | 2022 |
| Virtual dictionary based kernel sparse representation for face recognition Z Fan, D Zhang, X Wang, Q Zhu, Y Wang Pattern Recognition 76, 1-13, 2018 | 49 | 2018 |
| Non-negative discriminative brain functional connectivity for identifying schizophrenia on resting-state fMRI Q Zhu, J Huang, X Xu Biomedical engineering online 17, 1-15, 2018 | 42 | 2018 |
| Manifold discriminant regression learning for image classification Y Lu, Z Lai, Z Fan, J Cui, Q Zhu Neurocomputing 166, 475-486, 2015 | 41 | 2015 |
| From the idea of “sparse representation” to a representation-based transformation method for feature extraction Y Xu, Q Zhu, Z Fan, Y Wang, JS Pan Neurocomputing 113, 168-176, 2013 | 40 | 2013 |
| Reformative nonlinear feature extraction using kernel MSE Q Zhu Neurocomputing 73 (16-18), 3334-3337, 2010 | 38 | 2010 |
| Identifying resting-state multifrequency biomarkers via tree-guided group sparse learning for schizophrenia classification J Huang, Q Zhu, X Hao, X Shi, S Gao, X Xu, D Zhang IEEE journal of biomedical and health informatics 23 (1), 342-350, 2018 | 35 | 2018 |
| Modified minimum squared error algorithm for robust classification and face recognition experiments Y Xu, X Fang, Q Zhu, Y Chen, J You, H Liu Neurocomputing 135, 253-261, 2014 | 35 | 2014 |
| Multi-modal AD classification via self-paced latent correlation analysis Q Zhu, N Yuan, J Huang, X Hao, D Zhang Neurocomputing 355, 143-154, 2019 | 33 | 2019 |
Daoqiang ZhangNanjing University of Aeronautics and AstronauticsVerified email at nuaa.edu.cn
