| Fingerprint classification based on depth neural network R Wang, C Han, Y Wu, T Guo arXiv preprint arXiv:1409.5188, 2014 | 66 | 2014 |
| A novel fingerprint classification method based on deep learning R Wang, C Han, T Guo 2016 23rd International Conference on Pattern Recognition (ICPR), 931-936, 2016 | 43 | 2016 |
| Parallel algorithms for large-scale linearly constrained minimization problem C Han, F Zheng, T Guo, G He Acta Mathematicae Applicatae Sinica, English Series 30 (3), 707-720, 2014 | 27 | 2014 |
| Solving combinatorial problems with machine learning methods T Guo, C Han, S Tang, M Ding Nonlinear Combinatorial Optimization, 207-229, 2019 | 23 | 2019 |
| A novel method based on deep learning for aligned fingerprints matching Y Liu, B Zhou, C Han, T Guo, J Qin Applied Intelligence 50, 397-416, 2020 | 20 | 2020 |
| A new onestep smoothing newton method for the secondorder cone complementarity problem L Fang, C Han Mathematical methods in the applied sciences 34 (3), 347-359, 2011 | 19 | 2011 |
| Parallel variable distribution algorithm for constrained optimization with nonmonotone technique C Han, T Feng, G He, T Guo Journal of Applied Mathematics 2013, 2013 | 17 | 2013 |
| Parallel SSLE algorithm for large scale constrained optimization F Zheng, C Han, Y Wang Applied Mathematics and Computation 217 (12), 5377-5384, 2011 | 17 | 2011 |
| Fast minutiae extractor using neural network B Zhou, C Han, Y Liu, T Guo, J Qin Pattern Recognition 103, 107273, 2020 | 15 | 2020 |
| Convergence of stochastic gradient descent in deep neural network B Zhou, C Han, T Guo Acta Mathematicae Applicatae Sinica, English Series 37 (1), 126-136, 2021 | 12 | 2021 |
| On the convergence of asynchronous parallel algorithm for large-scale linearly constrained minimization problem C Han, Y Wang, G He Applied Mathematics and Computation 211 (2), 434-441, 2009 | 12 | 2009 |
| A method for singular points detection based on faster-RCNN Y Liu, B Zhou, C Han, T Guo, J Qin Applied Sciences 8 (10), 1853, 2018 | 11 | 2018 |
| Shrinking gradient descent algorithms for total variation regularized image denoising M Li, C Han, R Wang, T Guo Computational Optimization and Applications 68, 643-660, 2017 | 10 | 2017 |
| ExSinGAN: Learning an explainable generative model from a single image ZC Zhang, CY Han, TD Guo arXiv preprint arXiv:2105.07350, 2021 | 9 | 2021 |
| Partial fingerprint matching via phase-only correlation and deep convolutional neural network J Qin, S Tang, C Han, T Guo Neural Information Processing: 24th International Conference, ICONIP 2017 …, 2017 | 8 | 2017 |
| Multi-scaling detection of singular points based on fully convolutional networks in fingerprint images J Qin, C Han, C Bai, T Guo Biometric Recognition: 12th Chinese Conference, CCBR 2017, Shenzhen, China …, 2017 | 8 | 2017 |
| An NMF-based method for the fingerprint orientation field estimation G Shao, C Han, T Guo, Y Hao Computer and Information Science 2012, 93-104, 2012 | 8 | 2012 |
| Enhancing hyperspectral unmixing with two-stage multiplicative update nonnegative matrix factorization L Sun, K Zhao, C Han, Z Liu IEEE Access 7, 171023-171031, 2019 | 7 | 2019 |
| Energy losses and voltage stability study in distribution network with distributed generation H Ren, C Han, T Guo, W Pei Journal of Applied Mathematics 2014, 2014 | 7 | 2014 |
| An Energy-Based Centrality for Electrical Networks R Kong, C Han, T Guo, W Pei Energy and Power Engineering 5 (04), 597, 2013 | 7 | 2013 |
