| Deep Speech 2: End-to-End Speech Recognition in English and Mandarin D Amodei, R Anubhai, E Battenberg, C Case, J Casper, B Catanzaro, ... International Conference on Machine Learning (ICML), 2015 | 3942 | 2015 |
| Deep Speaker: an End-to-End Neural Speaker Embedding System C Li, X Ma, B Jiang, X Li, X Zhang, X Liu, Y Cao, A Kannan, Z Zhu arXiv preprint arXiv:1705.02304, 2017 | 598 | 2017 |
| Deep learning identity-preserving face space Z Zhu, P Luo, X Wang, X Tang 2013 IEEE International Conference on Computer Vision (ICCV), 113-120, 2013 | 404 | 2013 |
| Multi-view perceptron: a deep model for learning face identity and view representations Z Zhu, P Luo, X Wang, X Tang Advances in Neural Information Processing Systems (NIPS), 217-225, 2014 | 314 | 2014 |
| Fully supervised speaker diarization A Zhang, Q Wang, Z Zhu, J Paisley, C Wang ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 286 | 2019 |
| Exploring Neural Transducers for End-to-End Speech Recognition E Battenberg, J Chen, R Child, A Coates, Y Gaur, Y Li, H Liu, S Satheesh, ... Automatic Speech Recognition and Understanding (ASRU) 2017, 2017 | 267 | 2017 |
| Face Model Compression by Distilling Knowledge from Neurons. P Luo, Z Zhu, Z Liu, X Wang, X Tang The AAAI Conference on Artificial Intelligence (AAAI) 2016, 3560-3566, 2015 | 253 | 2015 |
| DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection W Ouyang, P Luo, X Zeng, S Qiu, Y Tian, H Li, S Yang, Z Wang, Y Xiong, ... arXiv preprint arXiv:1409.3505, 2014 | 178 | 2014 |
| Recover canonical-view faces in the wild with deep neural networks Z Zhu, P Luo, X Wang, X Tang arXiv preprint arXiv:1404.3543, 2014 | 159 | 2014 |
| Deployed end-to-end speech recognition B Catanzaro, J Chen, M Chrzanowski, E Elsen, J Engel, C Fougner, ... US Patent App. 10/319,374, 2019 | 139 | 2019 |
| End-to-end speech recognition B Catanzaro, J Chen, M Chrzanowski, E Elsen, J Engel, C Fougner, ... US Patent 10,332,509, 2019 | 123 | 2019 |
| Learning Multiscale Features Directly From Waveforms Z Zhu, JH Engel, A Hannun International Speech Communication Association (Interspeech) 2016, 2016 | 89 | 2016 |
| Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling H Liu, Z Zhu, X Li, S Satheesh International Conference on Machine Learning (ICML), 2017, 2017 | 65 | 2017 |
| Methods and systems for verifying face images based on canonical images X Tang, ZHU Zhenyao, P Luo, X Wang US Patent 10,037,457, 2018 | 61* | 2018 |
| Deep learning multi-view representation for face recognition Z Zhu, P Luo, X Wang, X Tang arXiv preprint arXiv:1406.6947, 2014 | 42 | 2014 |
| Systems and methods for principled bias reduction in production speech models E Battenberg, R CHILD, A Coates, C Fougner, G Yashesh, J Huang, ... US Patent App. 15/884,239, 2018 | 17 | 2018 |
| Deep Generative and Discriminative Domain Adaptation H Zhao, J Hu, Z Zhu, A Coates, G Gordon Proceedings of the 18th International Conference on Autonomous Agents and …, 2019 | 10 | 2019 |
| Systems and methods for automatic unit selection and target decomposition for sequence labelling H Liu, ZHU Zhenyao, S Satheesh US Patent 10,373,610, 2019 | 9 | 2019 |
| Reducing Bias in Production Speech Models E Battenberg, R Child, A Coates, C Fougner, Y Gaur, J Huang, H Jun, ... arXiv preprint arXiv:1705.04400, 2017 | 8 | 2017 |
| Method and system for exacting face features from data of face images X Tang, ZHU Zhenyao, P Luo, X Wang US Patent 9,710,697, 2017 | 7 | 2017 |
Xiaoou TangThe Chinese University of Hong KongDirección de correo verificada de ie.cuhk.edu.hk
