| Selecting a reference high resolution for fingerprint recognition using minutiae and pores D Zhang, F Liu, Q Zhao, G Lu, N Luo IEEE Transactions on Instrumentation and Measurement 60 (3), 863-871, 2010 | 121 | 2010 |
| Study on novel curvature features for 3D fingerprint recognition F Liu, D Zhang, L Shen Neurocomputing 168, 599-608, 2015 | 82 | 2015 |
| Ensemble one-dimensional convolution neural networks for skeleton-based action recognition Y Xu, J Cheng, L Wang, H Xia, F Liu, D Tao IEEE Signal Processing Letters 25 (7), 1044-1048, 2018 | 76 | 2018 |
| 3D fingerprint reconstruction system using feature correspondences and prior estimated finger model F Liu, D Zhang Pattern Recognition 47 (1), 178-193, 2014 | 74 | 2014 |
| Robust and high-security fingerprint recognition system using optical coherence tomography F Liu, G Liu, Q Zhao, L Shen Neurocomputing 402, 14-28, 2020 | 51 | 2020 |
| A novel hierarchical fingerprint matching approach F Liu, Q Zhao, D Zhang Pattern Recognition 44 (8), 1604-1613, 2011 | 51 | 2011 |
| Policies, applications, barriers and future trends of building information modeling technology for building sustainability and informatization in China M Xie, Y Qiu, Y Liang, Y Zhou, Z Liu, G Zhang Energy Reports 8, 7107-7126, 2022 | 46 | 2022 |
| High-accurate and robust fingerprint anti-spoofing system using optical coherence tomography F Liu, G Liu, X Wang Expert Systems with Applications 130, 31-44, 2019 | 45 | 2019 |
| Fingerprint pore matching based on sparse representation F Liu, Q Zhao, L Zhang, D Zhang 2010 20th International Conference on Pattern Recognition, 1630-1633, 2010 | 44 | 2010 |
| A flexible touch-based fingerprint acquisition device and a benchmark database using optical coherence tomography F Liu, C Shen, H Liu, G Liu, Y Liu, Z Guo, L Wang IEEE Transactions on Instrumentation and Measurement 69 (9), 6518-6529, 2020 | 43 | 2020 |
| Breast cancer discriminant feature analysis for diagnosis via jointly sparse learning H Kong, Z Lai, X Wang, F Liu Neurocomputing 177, 198-205, 2016 | 42 | 2016 |
| Class-specific random forest with cross-correlation constraints for spectral–spatial hyperspectral image classification Z Liu, B Tang, X He, Q Qiu, F Liu IEEE Geoscience and Remote Sensing Letters 14 (2), 257-261, 2017 | 36 | 2017 |
| One-class fingerprint presentation attack detection using auto-encoder network F Liu, H Liu, W Zhang, G Liu, L Shen IEEE Transactions on Image Processing 30, 2394-2407, 2021 | 32 | 2021 |
| A joint-L2, 1-norm-constraint-based semi-supervised feature extraction for RNA-Seq data analysis JX Liu, D Wang, YL Gao, CH Zheng, JL Shang, F Liu, Y Xu Neurocomputing 228, 263-269, 2017 | 32 | 2017 |
| A comparative study on quality assessment of high resolution fingerprint images Q Zhao, F Liu, L Zhang, D Zhang 2010 IEEE international conference on image processing, 3089-3092, 2010 | 25 | 2010 |
| Fingerprint pore matching using deep features F Liu, Y Zhao, G Liu, L Shen Pattern Recognition 102, 107208, 2020 | 24 | 2020 |
| Fingerprint pore comparison using local features and spatial relations Y Xu, G Lu, Y Lu, F Liu, D Zhang IEEE Transactions on Circuits and Systems for Video Technology 29 (10), 2927 …, 2018 | 22 | 2018 |
| Case study of 3D fingerprints applications F Liu, J Liang, L Shen, M Yang, D Zhang, Z Lai PLoS One 12 (4), e0175261, 2017 | 17 | 2017 |
| Feature guided fingerprint pore matching F Liu, Y Zhao, L Shen Biometric Recognition: 12th Chinese Conference, CCBR 2017, Shenzhen, China …, 2017 | 11 | 2017 |
| Fingerprint pore extraction based on multi-scale morphology Y Xu, G Lu, F Liu, Y Li Biometric Recognition: 12th Chinese Conference, CCBR 2017, Shenzhen, China …, 2017 | 11 | 2017 |
