| An improved failure mode and effects analysis method based on uncertainty measure in the evidence theory D Wu, Y Tang Quality and Reliability Engineering International 36 (5), 1786-1807, 2020 | 80 | 2020 |
| Revisiting consistency regularization for deep partial label learning DD Wu, DB Wang, ML Zhang International conference on machine learning, 24212-24225, 2022 | 55 | 2022 |
| A new approach for generation of generalized basic probability assignment in the evidence theory Y Tang, D Wu, Z Liu Pattern Analysis and Applications 24 (3), 1007-1023, 2021 | 49 | 2021 |
| A new classification method based on the negation of a basic probability assignment in the evidence theory D Wu, Z Liu, Y Tang Engineering Applications of Artificial Intelligence 96, 103985, 2020 | 49 | 2020 |
| Robust representation learning for unreliable partial label learning Y Shi, DD Wu, X Geng, ML Zhang arXiv preprint arXiv:2308.16718, 2023 | 3 | 2023 |
| Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning DD Wu, DB Wang, ML Zhang Proceedings of the AAAI Conference on Artificial Intelligence 38 (14), 15888 …, 2024 | | 2024 |
| Efficient Model Stealing Defense with Noise Transition Matrix DD Wu, C Fu, W Wu, W Xia, X Zhang, J Zhou, ML Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
| A natural language processing-based approach: mapping human perception by understanding deep semantic features in street view images H Ma, D Wu arXiv preprint arXiv:2311.17354, 2023 | | 2023 |
Yongchuan TangNorthwestern Polytechnical University在 mail.nwpu.edu.cn 的电子邮件经过验证
