| Learning to incorporate structure knowledge for image inpainting J Yang, Z Qi, Y Shi Proceedings of the AAAI conference on artificial intelligence 34 (07), 12605 …, 2020 | 146 | 2020 |
| Unsupervised anomaly segmentation via deep feature reconstruction Y Shi, J Yang, Z Qi Neurocomputing 424, 9-22, 2021 | 142 | 2021 |
| Dfr: Deep feature reconstruction for unsupervised anomaly segmentation J Yang, Y Shi, Z Qi arXiv preprint arXiv:2012.07122, 2020 | 77 | 2020 |
| Visual anomaly detection for images: A systematic survey J Yang, R Xu, Z Qi, Y Shi Procedia computer science 199, 471-478, 2022 | 51 | 2022 |
| Visual anomaly detection for images: A survey J Yang, R Xu, Z Qi, Y Shi arXiv preprint arXiv:2109.13157, 2021 | 50 | 2021 |
| Learning deep feature correspondence for unsupervised anomaly detection and segmentation J Yang, Y Shi, Z Qi Pattern Recognition 132, 108874, 2022 | 42 | 2022 |
| Water distribution network modeling based on NARX X Zhe, Y Jie, C Huaqiang, K Yaguang, H Bishi IFAC-PapersOnLine 48 (11), 72-77, 2015 | 15 | 2015 |
| Deep Learning Based Image Quality Assessment: A Survey J Yang, M Lyu, Z Qi, Y Shi Procedia Computer Science 221, 1000-1005, 2023 | 14 | 2023 |
| Rethinking lightweight convolutional neural networks for efficient and high-quality pavement crack detection K Li, J Yang, S Ma, B Wang, S Wang, Y Tian, Z Qi IEEE Transactions on Intelligent Transportation Systems 25 (1), 237-250, 2024 | 10 | 2024 |
| Rigid pairwise 3D point cloud registration: a survey M Lyu, J Yang, Z Qi, R Xu, J Liu Pattern Recognition, 110408, 2024 | 6 | 2024 |
| Deep feature inpainting for unsupervised visual anomaly detection J Yang, M Lyu, Z Qi, Y Tian, Y Shi Procedia Computer Science 221, 901-911, 2023 | 1 | 2023 |
zhiquan qi, 齐志泉University of Chinese Academy of SciencesEmail yang diverifikasi di ucas.ac.cn