Deephunter: a coverage-guided fuzz testing framework for deep neural networks X Xie, L Ma, F Juefei-Xu, M Xue, H Chen, Y Liu, J Zhao, B Li, J Yin, S See Proceedings of the 28th ACM SIGSOFT international symposium on software …, 2019 | 464* | 2019 |
Arid: A new dataset for recognizing action in the dark Y Xu, J Yang, H Cao, K Mao, J Yin, S See Deep Learning for Human Activity Recognition: Second International Workshop …, 2021 | 54 | 2021 |
Improving deep lesion detection using 3D contextual and spatial attention Q Tao, Z Ge, J Cai, J Yin, S See Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 41 | 2019 |
Act: an attentive convolutional transformer for efficient text classification P Li, P Zhong, K Mao, D Wang, X Yang, Y Liu, J Yin, S See Proceedings of the AAAI conference on artificial intelligence 35 (15), 13261 …, 2021 | 38 | 2021 |
Aligning correlation information for domain adaptation in action recognition Y Xu, H Cao, K Mao, Z Chen, L Xie, J Yang IEEE Transactions on Neural Networks and Learning Systems, 2022 | 37 | 2022 |
Secure deep learning engineering: A software quality assurance perspective L Ma, F Juefei-Xu, M Xue, Q Hu, S Chen, B Li, Y Liu, J Zhao, J Yin, S See arXiv preprint arXiv:1810.04538, 2018 | 37 | 2018 |
Mlmodelci: An automatic cloud platform for efficient mlaas H Zhang, Y Li, Y Huang, Y Wen, J Yin, K Guan Proceedings of the 28th ACM International Conference on Multimedia, 4453-4456, 2020 | 24 | 2020 |
Continual semantic segmentation with automatic memory sample selection L Zhu, T Chen, J Yin, S See, J Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 19 | 2023 |
Cloud3DView: An interactive tool for cloud data center operations J Yin, P Sun, Y Wen, H Gong, M Liu, X Li, H You, J Gao, C Lin Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM, 499-500, 2013 | 19 | 2013 |
Fast MPEG-CDVS encoder with GPU-CPU hybrid computing LY Duan, W Sun, X Zhang, S Wang, J Chen, J Yin, S See, T Huang, ... IEEE Transactions on Image Processing 27 (5), 2201-2216, 2018 | 15 | 2018 |
Stochastic downsampling for cost-adjustable inference and improved regularization in convolutional networks J Kuen, X Kong, Z Lin, G Wang, J Yin, S See, YP Tan Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 15 | 2018 |
Effective action recognition with embedded key point shifts H Cao, Y Xu, J Yang, K Mao, J Yin, S See Pattern Recognition 120, 108172, 2021 | 8 | 2021 |
Exploiting inter-frame regional correlation for efficient action recognition Y Xu, J Yang, K Mao, J Yin, S See Expert Systems with Applications 178, 114829, 2021 | 7 | 2021 |
Inferbench: Understanding deep learning inference serving with an automatic benchmarking system H Zhang, Y Huang, Y Wen, J Yin, K Guan arXiv preprint arXiv:2011.02327, 2020 | 6 | 2020 |
A context-rich and extensible framework for spontaneous smartphone networking E Talipov, J Yin, Y Chon, H Cha Computer communications 37, 25-39, 2014 | 6 | 2014 |
Learning gabor texture features for fine-grained recognition L Zhu, T Chen, J Yin, S See, J Liu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 5 | 2023 |
PNL: Efficient long-range dependencies extraction with pyramid non-local module for action recognition Y Xu, H Cao, J Yang, K Mao, J Yin, S See Neurocomputing 447, 282-293, 2021 | 5 | 2021 |
Saving the limping: Fault-tolerant quadruped locomotion via reinforcement learning D Liu, T Zhang, J Yin, S See arXiv preprint arXiv:2210.00474, 2022 | 4 | 2022 |
Self-supervised video representation learning by video incoherence detection H Cao, Y Xu, K Mao, L Xie, J Yin, S See, Q Xu, J Yang IEEE Transactions on Cybernetics, 2023 | 2 | 2023 |
MIGPerf: A Comprehensive Benchmark for Deep Learning Training and Inference Workloads on Multi-Instance GPUs H Zhang, Y Li, W Xiao, Y Huang, X Di, J Yin, S See, Y Luo, CT Lau, Y You arXiv preprint arXiv:2301.00407, 2023 | 2 | 2023 |