| E-RNN: Design optimization for efficient recurrent neural networks in FPGAs Z Li, C Ding, S Wang, W Wen, Y Zhuo, C Liu, Q Qiu, W Xu, X Lin, X Qian, ... 2019 IEEE International Symposium on High Performance Computer Architecture …, 2019 | 78 | 2019 |
| Ecacl: A holistic framework for semi-supervised domain adaptation K Li, C Liu, H Zhao, Y Zhang, Y Fu Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 55 | 2021 |
| Image as Set of Points X Ma, Y Zhou, H Wang, C Qin, B Sun, C Liu, Y Fu ICLR'23, code: https://github.com/ma-xu/Context-Cluster, 2023 | 34 | 2023 |
| Automatic localization and identification of mitochondria in cellular electron cryo-tomography using faster-RCNN R Li, X Zeng, SE Sigmund, R Lin, B Zhou, C Liu, K Wang, R Jiang, ... BMC bioinformatics 20, 75-85, 2019 | 32 | 2019 |
| Hyperstar: Task-aware hyperparameters for deep networks G Mittal, C Liu, N Karianakis, V Fragoso, M Chen, Y Fu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 29 | 2020 |
| Domain Generalization via Feature Variation Decorrelation C Liu, L Wang, K Li, Y Fu Proceedings of the 29th ACM International Conference on Multimedia, 1683-1691, 2021 | 19 | 2021 |
| Test-time fourier style calibration for domain generalization X Zhao, C Liu, A Sicilia, SJ Hwang, Y Fu IJCAI'22, 2022 | 17 | 2022 |
| Learning to learn across diverse data biases in deep face recognition C Liu, X Yu, YH Tsai, M Faraki, R Moslemi, M Chandraker, Y Fu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 15 | 2022 |
| Deep learning based supervised semantic segmentation of electron cryo-subtomograms C Liu, X Zeng, R Lin, X Liang, Z Freyberg, E Xing, M Xu 2018 25th IEEE International Conference on Image Processing (ICIP), 1578-1582, 2018 | 15 | 2018 |
| Multi-task Learning for Macromolecule Classification, Segmentation and Coarse Structural Recovery in Cryo-Tomography C Liu, X Zeng, K Wang, Q Guo, M Xu British Machine Vision Conference (BMVC) 2018, 1007, 2018 | 13 | 2018 |
| Discovering Informative and Robust Positives for Video Domain Adaptation C Liu, K Li, M Stopa, J Amano, Y Fu ICLR'23, 2023 | 6 | 2023 |
| Meta adversarial weight for unsupervised domain adaptation C Liu, L Wang, Y Fu Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022 | 5 | 2022 |
| Semi-supervised domain adaptation with prototypical alignment and consistency learning K Li, C Liu, H Zhao, Y Zhang, Y Fu | 4 | 2020 |
| Arena: Adaptive real-time update anomaly prediction in cloud systems S Huang, C Fung, C Liu, S Zhang, G Wei, Z Luan, D Qian 2017 13th International Conference on Network and Service Management (CNSM), 1-9, 2017 | 4 | 2017 |
| Guided graph attention learning for video-text matching K Li, C Liu, M Stopa, J Amano, Y Fu ACM Transactions on Multimedia Computing, Communications and Applications 18 …, 2023 | 2 | 2023 |
| Task-aware recommendation of hyperparameter configurations G Mittal, VMF ROJAS, N Karianakis, M Chen, C Liu US Patent 11,544,561, 2023 | 2 | 2023 |
| Frame Flexible Network Y Zhang, Y Bai, C Liu, H Wang, S Li, Y Fu CVPR'23 https://github.com/BeSpontaneous/FFN-pytorch, 2023 | 1 | 2023 |
| Domain generalized margin via meta-learning for deep face recognition X Yu, YH Tsai, M Faraki, R Moslemi, M Chandraker, C Liu US Patent App. 17/521,252, 2022 | 1 | 2022 |
| HyperSTAR: Task-Aware Hyperparameter Recommendation for Training and Compression C Liu, G Mittal, N Karianakis, V Fragoso, Y Yu, Y Fu, M Chen International Journal of Computer Vision, 1-15, 2023 | | 2023 |
| Rethinking Neighborhood Consistency Learning on Unsupervised Domain Adaptation C Liu, L Wang, Y Fu Proceedings of the 31st ACM International Conference on Multimedia, 7247-7254, 2023 | | 2023 |
Yun Raymond FuNEU, COE Distinguished Professor; MAE, FNAI, FAAAS, FIEEE, FSPIE, FOSA, FIAPRVerified email at neu.edu
