| On-demand deep model compression for mobile devices: A usage-driven model selection framework S Liu, Y Lin, Z Zhou, K Nan, H Liu, J Du MobiSys-2018, 389-400, 2018 | 228 | 2018 |
| Privacy Adversarial Network: Representation Learning for Mobile Data Privacy S Liu, J Du, A Shrivastava, L Zhong Ubicomp-2020 3 (4), 1-18, 2019 | 51 | 2019 |
| Deep model compression for mobile platforms: A survey K Nan, S Liu, J Du, H Liu Tsinghua Science and Technology-2018 24 (6), 677-693, 2019 | 47 | 2019 |
| Ubiear: Bringing location-independent sound awareness to the hard-of-hearing people with smartphones L Sicong, Z Zimu, D Junzhao, S Longfei, J Han, X Wang Ubicomp-2017-Distinguished Paper Award 1 (2), 1-21, 2017 | 45 | 2017 |
| Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic Y Zhang, B Guo, Y Ding, J Liu, C Qiu, S Liu, Z Yu Information Processing & Management 59 (3), 102935, 2022 | 26 | 2022 |
| AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles S Liu, J Du, K Nan, A Wang, Y Lin IEEE Transactions on Mobile Computing (TMC)-2020, 2020 | 25 | 2020 |
| AdaSpring: Context-adaptive and Runtime-evolutionary Deep Model Compression for Mobile Applications S Liu, B Guo, K Ma, Z Yu, J Du Ubicomp-2021 5 (1), 1-22, 2021 | 20 | 2021 |
| Towards information-rich, logical dialogue systems with knowledge-enhanced neural models H Wang, B Guo, W Wu, S Liu, Z Yu Neurocomputing 465, 248-264, 2021 | 15 | 2021 |
| Decentralized multi-agv task allocation based on multi-agent reinforcement learning with information potential field rewards M Li, B Guo, J Zhang, J Liu, S Liu, Z Yu, Z Li, L Xiang 2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems …, 2021 | 15 | 2021 |
| CrowdHMT: crowd intelligence with the deep fusion of human, machine, and IoT B Guo, Y Liu, S Liu, Z Yu, X Zhou IEEE Internet of Things Journal 9 (24), 24822-24842, 2022 | 14 | 2022 |
| Better accuracy with quantified privacy: representations learned via reconstructive adversarial network S Liu, A Shrivastava, J Du, L Zhong arXiv preprint arXiv:1901.08730, 2019 | 13 | 2019 |
| Mobiear-building an environment-independent acoustic sensing platform for the deaf using deep learning S Liu, J Du MobiSys-2016, 50-50, 2016 | 13* | 2016 |
| Energy-efficient algorithm to construct the information potential field in WSNs S Liu, J Du, H Liu, R Li, X Yang, K Sha IEEE Sensors Journal-2017(IF:3.301) 17 (12), 3822-3831, 2017 | 12 | 2017 |
| Context-aware adaptive surgery: A fast and effective framework for adaptative model partition H Wang, B Guo, J Liu, S Liu, Y Wu, Z Yu Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2021 | 11 | 2021 |
| TL-SDD: A Transfer Learning-Based Method for Surface Defect Detection with Few Samples J Cheng, B Guo, J Liu, S Liu, G Wu, Y Sun, Z Yu BigCom-2021, 2021 | 10 | 2021 |
| Air pollution source estimation profiling via mobile sensor networks X Yang, J Du, S Liu, R Li, H Liu CITS-2016, 1-5, 2016 | 9 | 2016 |
| SmartCare: energy-efficient long-term physical activity tracking using smartphones H Liu, R Li, S Liu, S Tian, J Du Tsinghua Science and Technology 20 (4), 348-363, 2015 | 7 | 2015 |
| Fedaux: An efficient framework for hybrid federated learning H Gu, B Guo, J Wang, W Sun, J Liu, S Liu, Z Yu ICC 2022-IEEE International Conference on Communications, 195-200, 2022 | 6 | 2022 |
| Adaenlight: Energy-aware low-light video stream enhancement on mobile devices S Liu, X Li, Z Zhou, B Guo, M Zhang, H Shen, Z Yu Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2023 | 4 | 2023 |
| CAQ: Towards Context-aware and Self-adaptive Deep Model Computation for AIoT Applications Sicong Liu, Yungang Wu, Bin Guo, Yuzhan Wang, Ke Ma, Liyao Xiang, Zhetao Li ... IEEE Internet of Things Journal, 2022 | 3 | 2022 |
Bin GuoProfessor of Computer Science, Northwestern Polytechnical UniversityE-mail confirmado em nwpu.edu.cn
