| Drawing and recognizing chinese characters with recurrent neural network XY Zhang, F Yin, YM Zhang, CL Liu, Y Bengio IEEE transactions on pattern analysis and machine intelligence 40 (4), 849-862, 2017 | 394 | 2017 |
| Deep hyperspherical learning W Liu, YM Zhang, X Li, Z Yu, B Dai, T Zhao, L Song Advances in neural information processing systems 30, 2017 | 152 | 2017 |
| Bag of Tricks for 3D MRI Brain Tumor Segmentation YX Zhao, YM Zhang, CL Liu MICCAI workshop, 2019 | 137 | 2019 |
| Fast kNN Graph Construction with Locality Sensitive Hashing YM Zhang, K Huang, G Geng, CL Liu Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013 | 127 | 2013 |
| Handwritten mathematical expression recognition via paired adversarial learning JW Wu, F Yin, YM Zhang, XY Zhang, CL Liu International Journal of Computer Vision 128, 2386-2401, 2020 | 107 | 2020 |
| Image-to-markup generation via paired adversarial learning JW Wu, F Yin, YM Zhang, XY Zhang, CL Liu Machine learning and knowledge discovery in databases: European conference …, 2019 | 69 | 2019 |
| Adaptive spatial pooling for image classification Y Liu, YM Zhang, XY Zhang, CL Liu Pattern Recognition 55, 58-67, 2016 | 55 | 2016 |
| Graph-to-graph: towards accurate and interpretable online handwritten mathematical expression recognition JW Wu, F Yin, YM Zhang, XY Zhang, CL Liu Proceedings of the AAAI Conference on Artificial Intelligence 35 (4), 2925-2933, 2021 | 42 | 2021 |
| Multi-view semi-supervised 3D whole brain segmentation with a self-ensemble network YX Zhao, YM Zhang, M Song, CL Liu Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 42 | 2019 |
| Learning locality preserving graph from data YM Zhang, K Huang, X Hou, CL Liu IEEE transactions on cybernetics 44 (11), 2088-2098, 2014 | 40 | 2014 |
| Anomaly detection via minimum likelihood generative adversarial networks C Wang, YM Zhang, CL Liu 2018 24th International Conference on Pattern Recognition (ICPR), 1121-1126, 2018 | 36 | 2018 |
| Recurrent hidden semi-markov model H Dai, B Dai, YM Zhang, S Li, L Song International Conference on Learning Representations, 2022 | 34 | 2022 |
| Minimum-risk training for semi-Markov conditional random fields with application to handwritten Chinese/Japanese text recognition XD Zhou, YM Zhang, F Tian, HA Wang, CL Liu Pattern Recognition 47 (5), 1904-1916, 2014 | 32 | 2014 |
| Instance GNN: a learning framework for joint symbol segmentation and recognition in online handwritten diagrams XL Yun, YM Zhang, F Yin, CL Liu IEEE Transactions on Multimedia 24, 2580-2594, 2021 | 29 | 2021 |
| Combating phishing attacks via brand identity and authorization features GG Geng, XD Lee, YM Zhang Security and communication networks 8 (6), 888-898, 2015 | 29 | 2015 |
| MTC: A fast and robust graph-based transductive learning method YM Zhang, K Huang, GG Geng, CL Liu IEEE transactions on neural networks and learning systems 26 (9), 1979-1991, 2014 | 29 | 2014 |
| Online semi-supervised learning with learning vector quantization YY Shen, YM Zhang, XY Zhang, CL Liu Neurocomputing 399, 467-478, 2020 | 24 | 2020 |
| Joint training of conditional random fields and neural networks for stroke classification in online handwritten documents JY Ye, YM Zhang, CL Liu 2016 23rd International Conference on Pattern Recognition (ICPR), 3264-3269, 2016 | 23 | 2016 |
| Contextual stroke classification in online handwritten documents with graph attention networks JY Ye, YM Zhang, Q Yang, CL Liu 2019 International conference on document analysis and recognition (ICDAR …, 2019 | 21 | 2019 |
| Fast and robust graph-based transductive learning via minimum tree cut YM Zhang, K Huang, CL Liu 2011 IEEE 11th International Conference on Data Mining, 952-961, 2011 | 21 | 2011 |
Kaizhu HuangProfessor of ECE, Duke Kunshan UniversityVerified email at dukekunshan.edu.cn
