| Real-time trajectory planning for autonomous urban driving: Framework, algorithms, and verifications X Li, Z Sun, D Cao, Z He, Q Zhu IEEE/ASME Transactions on mechatronics 21 (2), 740-753, 2015 | 299 | 2015 |
| Wider and deeper, cheaper and faster: Tensorized lstms for sequence learning Z He, S Gao, L Xiao, D Liu, H He, D Barber Advances in Neural Information Processing Systems (NIPS), 1-11, 2017 | 73 | 2017 |
| Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers Z He, J Li, D Liu, H He, D Barber IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 1318-1327, 2019 | 62 | 2019 |
| A practical trajectory planning framework for autonomous ground vehicles driving in urban environments X Li, Z Sun, Z He, Q Zhu, D Liu IEEE Intelligent Vehicles Symposium (IV), 1160-1166, 2015 | 42 | 2015 |
| Robust road detection from a single image using road shape prior Z He, T Wu, Z Xiao, H He IEEE International Conference on Image Processing (ICIP), 2757-2761, 2013 | 42 | 2013 |
| MetaLogo: a heterogeneity-aware sequence logo generator and aligner Y Chen, Z He, Y Men, G Dong, S Hu, X Ying Briefings in Bioinformatics 23 (2), bbab591, 2022 | 8 | 2022 |
| Unsupervised multi-object detection for video surveillance using memory-based recurrent attention networks Z He, H He Symmetry 10 (9), 375, 2018 | 8 | 2018 |
| How does color constancy affect target recognition and instance segmentation? S Xue, S Gao, M Tan, Z He, L He Proceedings of the 29th ACM International Conference on Multimedia, 5537-5545, 2021 | 6 | 2021 |
| Unsupervised ensemble learning with noisy label correction X Zou, Z Zhang*, Z He*, L Shi* Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 6 | 2021 |
| Comprehensive strain-level analysis of the gut microbe Faecalibacterium prausnitzii in patients with liver cirrhosis Y Chen, P Liu, R Liu, S Hu, Z He, G Dong, C Feng, S An, X Ying Msystems 6 (4), 10.1128/msystems. 00775-21, 2021 | 4 | 2021 |
| Unsupervised continual learning of single-cell clustering based on novelty detection and memory replay P Ke#, S Xiang#, C Xie#, Y Zhang, Z He*, Z Zhang* 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2022 | 1 | 2022 |
| Towards Strain-Level Complexity: Sequencing Depth Required for Comprehensive Single-Nucleotide Polymorphism Analysis of the Human Gut Microbiome P Liu, S Hu, Z He, C Feng, G Dong, S An, R Liu, F Xu, Y Chen, X Ying Frontiers in Microbiology 13, 828254-828254, 2022 | 1 | 2022 |
| Multimedia Data Modelling Using Multidimensional Recurrent Neural Networks Z He, S Gao, L Xiao, D Liu, H He Symmetry 10 (9), 370, 2018 | 1 | 2018 |
| scDAC: deep adaptive clustering of single-cell transcriptomic data with coupled autoencoder and dirichlet process mixture model S An, J Shi, R Liu, Y Chen, J Wang, S Hu, X Xia, G Dong, X Bo, Z He, ... Bioinformatics, btae198, 2024 | | 2024 |
| Mosaic integration and knowledge transfer of single-cell multimodal data with MIDAS Z He, S Hu, Y Chen, S An, J Zhou, R Liu, J Shi, J Wang, G Dong, J Shi, ... Nature Biotechnology, 1-12, 2024 | | 2024 |
| A Joint Batch Correction and Adaptive Clustering Method of Single-Cell Transcriptomic Data S An, J Shi, R Liu, J Wang, S Hu, G Dong, X Ying, Z He Mathematics 11 (24), 4901, 2023 | | 2023 |
| VFA: a factor analysis algorithm for single-cell transcriptomic data based on the deep generative model R Liu, S An, S Hu, Y Chen, G Dong, Y Men, Z He*, X Ying* Military Medical Sciences 46 (9), 699-704, 2022 | | 2022 |
| Recurrent Neural Network Model for Rapid Identification of Coronavirus Sequences from High-Throughput Sequencing Data K Lu, S Hu, J Wu, P Liu, C Feng, Z He*, X Ying* Military Medical Sciences 44 (4), 253-257, 2020 | | 2020 |
| Deformable Part Model Based Crossroad Recognition for Unmanned Vehicles Z Xiao, T Wu, Z He, L Jin IEEE International Conference on Computer Sciences and Applications, 309-312, 2013 | | 2013 |
