| Feature distillation: Dnn-oriented jpeg compression against adversarial examples Z Liu, Q Liu, T Liu, N Xu, X Lin, Y Wang, W Wen 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR …, 2019 | 317 | 2019 |
| Security analysis and enhancement of model compressed deep learning systems under adversarial attacks Q Liu, T Liu, Z Liu, Y Wang, Y Jin, W Wen 2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC), 721-726, 2018 | 62 | 2018 |
| Machine vision guided 3d medical image compression for efficient transmission and accurate segmentation in the clouds Z Liu, X Xu, T Liu, Q Liu, Y Wang, Y Shi, W Wen, M Huang, H Yuan, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 47 | 2019 |
| StegoNet: Turn deep neural network into a stegomalware T Liu, Z Liu, Q Liu, W Wen, W Xu, M Li Proceedings of the 36th Annual Computer Security Applications Conference …, 2020 | 45 | 2020 |
| Concurrent weight encoding-based detection for bit-flip attack on neural network accelerators Q Liu, W Wen, Y Wang IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2020, 2020 | 36 | 2020 |
| Monitoring the health of emerging neural network accelerators with cost-effective concurrent test Q Liu, T Liu, Z Liu, W Wen, C Yang 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 14 | 2020 |
| {NeuroPots}: realtime proactive defense against {Bit-Flip} attacks in neural networks Q Liu, J Yin, W Wen, C Yang, S Sha 32nd USENIX Security Symposium (USENIX Security 23), 6347-6364, 2023 | 13 | 2023 |
| Defending deep learning-based biomedical image segmentation from adversarial attacks: a low-cost frequency refinement approach Q Liu, H Jiang, T Liu, Z Liu, S Li, W Wen, Y Shi Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 11 | 2020 |
| Neural pruning search for real-time object detection of autonomous vehicles P Zhao, G Yuan, Y Cai, W Niu, Q Liu, W Wen, B Ren, Y Wang, X Lin 2021 58th ACM/IEEE Design Automation Conference (DAC), 835-840, 2021 | 10 | 2021 |
| Model compression hardens deep neural networks: A new perspective to prevent adversarial attacks Q Liu, W Wen IEEE Transactions on Neural Networks and Learning Systems 34 (1), 3-14, 2021 | 8 | 2021 |
| Orchestrating medical image compression and remote segmentation networks Z Liu, S Li, Y Chen, T Liu, Q Liu, X Xu, Y Shi, W Wen Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 6 | 2020 |
| Safeguarding the intelligence of neural networks with built-in light-weight integrity marks (LIMA) FS Hosseini, Q Liu, F Meng, C Yang, W Wen 2021 IEEE International Symposium on Hardware Oriented Security and Trust …, 2021 | 5 | 2021 |
| A system-level perspective to understand the vulnerability of deep learning systems T Liu, N Xu, Q Liu, Y Wang, W Wen Proceedings of the 24th Asia and South Pacific Design Automation Conference …, 2019 | 5 | 2019 |
| Stealing your data from compressed machine learning models N Xu, Q Liu, T Liu, Z Liu, X Guo, W Wen 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 4 | 2020 |
| Enhancing the Robustness of Deep Neural Networks from" Smart" Compression T Liu, Z Liu, Q Liu, W Wen 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 528-532, 2018 | 2 | 2018 |
| Understanding adversarial attack and defense towards deep compressed neural networks Q Liu, T Liu, W Wen Cyber Sensing 2018 10630, 158-169, 2018 | 1 | 2018 |
| Ants: Attacking Spatial Temporal Graph Learning Networks Structurally R Ran, Q Liu, N Xu, N Sui, W Wen 2024 IEEE 48th Annual Computers, Software, and Applications Conference …, 2024 | | 2024 |
Wujie WenAssociate Professor, Department of Computer Science, NC State UniversityZweryfikowany adres z ncsu.edu