Scheduling policies for federated learning in wireless networks HH Yang, Z Liu, TQS Quek, HV Poor IEEE transactions on communications 68 (1), 317-333, 2019 | 585 | 2019 |
An unsupervised sentence embedding method by mutual information maximization Y Zhang, R He, Z Liu, KH Lim, L Bing arXiv preprint arXiv:2009.12061, 2020 | 181 | 2020 |
Track without appearance: Learn box and tracklet embedding with local and global motion patterns for vehicle tracking G Wang, R Gu, Z Liu, W Hu, M Song, JN Hwang Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 55 | 2021 |
Heterogeneous sensor data fusion by deep multimodal encoding Z Liu, W Zhang, S Lin, TQS Quek IEEE Journal of Selected Topics in Signal Processing 11 (3), 479-491, 2017 | 51 | 2017 |
Attention-based graph convolutional network for recommendation system C Feng, Z Liu, S Lin, TQS Quek ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 40 | 2019 |
Large‐Scale Far‐Infrared Invisibility Cloak Hiding Object from Thermal Detection L Shen, B Zheng, Z Liu, Z Wang, S Lin, S Dehdashti, E Li, H Chen Advanced Optical Materials 3 (12), 1738-1742, 2015 | 38 | 2015 |
Bootstrapped unsupervised sentence representation learning Y Zhang, R He, Z Liu, L Bing, H Li Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 35 | 2021 |
Toward clinically applicable 3-dimensional tooth segmentation via deep learning J Hao, W Liao, YL Zhang, J Peng, Z Zhao, Z Chen, BW Zhou, Y Feng, ... Journal of dental research 101 (3), 304-311, 2022 | 28 | 2022 |
Deep fusion of heterogeneous sensor data Z Liu, W Zhang, TQS Quek, S Lin 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 24 | 2017 |
Empirical study of zero-shot ner with chatgpt T Xie, Q Li, J Zhang, Y Zhang, Z Liu, H Wang Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023 | 18 | 2023 |
A chatgpt aided explainable framework for zero-shot medical image diagnosis J Liu, T Hu, Y Zhang, X Gai, Y Feng, Z Liu arXiv preprint arXiv:2307.01981, 2023 | 18 | 2023 |
Lightweight, dynamic graph convolutional networks for AMR-to-text generation Y Zhang, Z Guo, Z Teng, W Lu, SB Cohen, Z Liu, L Bing arXiv preprint arXiv:2010.04383, 2020 | 18 | 2020 |
Vprop: Variational inference using rmsprop ME Khan, Z Liu, V Tangkaratt, Y Gal arXiv preprint arXiv:1712.01038, 2017 | 17 | 2017 |
Variational adaptive-Newton method for explorative learning ME Khan, W Lin, V Tangkaratt, Z Liu, D Nielsen arXiv preprint arXiv:1711.05560, 2017 | 17 | 2017 |
Generate, discriminate and contrast: A semi-supervised sentence representation learning framework Y Chen, Y Zhang, B Wang, Z Liu, H Li arXiv preprint arXiv:2210.16798, 2022 | 16 | 2022 |
Hierarchical self-supervised learning for 3D tooth segmentation in intra-oral mesh scans Z Liu, X He, H Wang, H Xiong, Y Zhang, G Wang, J Hao, Y Feng, F Zhu, ... IEEE Transactions on Medical Imaging 42 (2), 467-480, 2022 | 13 | 2022 |
Towards calibrated hyper-sphere representation via distribution overlap coefficient for long-tailed learning H Wang, S Fu, X He, H Fang, Z Liu, H Hu European Conference on Computer Vision, 179-196, 2022 | 13 | 2022 |
Data fusion in wireless sensor networks: A statistical signal processing perspective D Ciuonzo, PS Rossi Institution of Engineering and Technology, 2019 | 13 | 2019 |
On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning J Bai, Z Liu, H Wang, J Hao, Y Feng, H Chu, H Hu The Eleventh International Conference on Learning Representations, 2022., 2023 | 12 | 2023 |
Hybrid-learning-based operational visual quality inspection for edge-computing-enabled IoT system Y Chu, D Feng, Z Liu, Z Zhao, Z Wang, XG Xia, TQS Quek IEEE Internet of Things Journal 9 (7), 4958-4972, 2021 | 11 | 2021 |