| Deep learning for monocular depth estimation: A review Y Ming, X Meng, C Fan, H Yu Neurocomputing 438, 14-33, 2021 | 274 | 2021 |
| Improving deep neural network with multiple parametric exponential linear units Y Li, C Fan, Y Li, Q Wu, Y Ming Neurocomputing 301, 11-24, 2018 | 92 | 2018 |
| Activity recognition from RGB-D camera with 3D local spatio-temporal features Y Ming, Q Ruan, AG Hauptmann 2012 IEEE international conference on multimedia and expo, 344-349, 2012 | 50 | 2012 |
| Stacked PCA network (SPCANet): an effective deep learning for face recognition L Tian, C Fan, Y Ming, Y Jin 2015 IEEE International Conference on Digital Signal Processing (DSP), 1039-1043, 2015 | 48 | 2015 |
| Robust regional bounding spherical descriptor for 3D face recognition and emotion analysis Y Ming Image and Vision Computing 35, 14-22, 2015 | 45 | 2015 |
| Rigid-area orthogonal spectral regression for efficient 3D face recognition Y Ming Neurocomputing 129, 445-457, 2014 | 41 | 2014 |
| 3D facial expression recognition based on basic geometric features X Li, Q Ruan, Y Ming IEEE 10th International Conference on Signal Processing Proceedings, 1366-1369, 2010 | 40 | 2010 |
| Robust sparse bounding sphere for 3D face recognition Y Ming, Q Ruan Image and Vision Computing 30 (8), 524-534, 2012 | 30 | 2012 |
| A Mandarin edutainment system integrated virtual learning environments Y Ming, Q Ruan, G Gao Speech Communication 55 (1), 71-83, 2013 | 29 | 2013 |
| Multiple scales combined principle component analysis deep learning network for face recognition L Tian, C Fan, Y Ming Journal of Electronic Imaging 25 (2), 023025-023025, 2016 | 28 | 2016 |
| 3D face recognition using corresponding point direction measure and depth local features X Wang, Q Ruan, Y Ming IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, 86-89, 2010 | 28 | 2010 |
| A face anti-spoofing method based on optical flow field W Yin, Y Ming, L Tian 2016 IEEE 13th International Conference on Signal Processing (ICSP), 1333-1337, 2016 | 26 | 2016 |
| Efficient Kernel discriminate spectral regression for 3D face recognition Y Ming, Q Ruan, X Li, M Mu IEEE 10th international conference on signal processing proceedings, 662-665, 2010 | 26 | 2010 |
| Uniform local binary pattern based texture-edge feature for 3D human behavior recognition Y Ming, G Wang, C Fan PloS one 10 (5), e0124640, 2015 | 24 | 2015 |
| 3D-TDC: A 3D temporal dilation convolution framework for video action recognition Y Ming, F Feng, C Li, JH Xue Neurocomputing 450, 362-371, 2021 | 22 | 2021 |
| CORNet: Context-based ordinal regression network for monocular depth estimation X Meng, C Fan, Y Ming, H Yu IEEE Transactions on Circuits and Systems for Video Technology 32 (7), 4841-4853, 2021 | 21 | 2021 |
| Mutual-learning sequence-level knowledge distillation for automatic speech recognition Z Li, Y Ming, L Yang, JH Xue Neurocomputing 428, 259-267, 2021 | 21 | 2021 |
| Trajectory image based dynamic gesture recognition with convolutional neural networks JT Hu, CX Fan, Y Ming 2015 15th International Conference on Control, Automation and Systems (ICCAS …, 2015 | 21 | 2015 |
| Visuals to text: A comprehensive review on automatic image captioning Y Ming, N Hu, C Fan, F Feng, J Zhou, H Yu IEEE/CAA Journal of Automatica Sinica 9 (8), 1339-1365, 2022 | 20 | 2022 |
| RFRN: A recurrent feature refinement network for accurate and efficient scene text detection G Deng, Y Ming, JH Xue Neurocomputing 453, 465-481, 2021 | 19 | 2021 |
