Scholar
xiang wei
Google Scholar ID: SydSP3gAAAAJ
北京交通大学
Citations & Impact
Citations
1,216
H-index
14
i10-index
20
Publications
20
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Publications:
- 1. Guo X, Wei X*, Zhang S, et al. DCRP: Class-Aware Feature Diffusion Constraint and Reliable Pseudo-Labeling for Imbalanced Semi-Supervised Learning[J]. IEEE Transactions on Multimedia, 2024. (SCI Q1)
- 2. Kong X, Wei X*, Liu X, Wang, J, Lu S, Xing, W, Lu W. FGBC: Flexible Graph-based Balanced Classifier for Class-imbalanced Semi-supervised Learning. Pattern Recognition. 2023. (SCI Q1)
- 3. Guo Xiaoyu; Wei Xiang*; Su Qi; Zhao Huiqin; Zhang Shunli; Prompt What You Need: Enhancing Segmentation in Rainy Scenes with Anchor-based Prompting, 2023 IEEE International Conference on Multimedia and Expo, grand challenges. (CCF-B, Won 1st place in Seeing Through the Rain (STRAIN): Vision Task Challenges in Real-world Rain Scenes in ICME 2023 Grand Challenges)
- 4. Wang Jingjie, Wei Xiang*, Lu Siyang, Wang Mingquan, Liu Xiaoyu, Lu Wei. Redesign Visual Transformer For Small Datasets, UIC 2022. (CCF-C)
- 5. Xiangyuan Kong, Xiang Wei*, Xiaoyu Liu, Jingjie Wang, Siyang Lu, Weiwei Xing, Wei Lu. 3LPR: A Three-stage Label Propagation and Reassignment Framework for Class-imbalanced Semi-supervised Learning. Knowledge-based systems. 2022. (SCI Q1)
- 6. Wei Xiang, WANG Jing-Jie, ZHANG Shun-Li, ZHANG Di, ZHANG Jian, WEI Xiao-Tao. ReLSL: Reliable Label Selection and Learning for Semi-Supervised Learning[J]. Journal of Computer Science and Technology, 2022. (CCF-A)
- 7. X. Wei, X. Wei, X. Kong, S. Lu, W. Xing, W. Lu, FMixCutMatch for semi-supervised deep learning. Neural Networks. 2020. (SCI Q1)
- 8. Guo X, Wei X*, Guo M, Wei X, Gao L, Xing W, Anomaly Detection of Trackside Equipment based on Semi-Supervised and Multi-Domain Learning. International conference on signal processing. 2020.
- 9. Wei X, Wei X*, Xing W, Lu S, Lu W, An Incremental Self-Labeling Strategy for Semi-supervised Deep Learning Based on Generative Adversarial Networks[J]. IEEE Access, 2020, PP(99):1-1.
- 10. Lu S, Wei X, Rao B, et al. LADRA: Log-based abnormal task detection and root-cause analysis in big data processing with Spark[J]. Future Generation Computer Systems, 2019, 95: 392-403.
- 11. Wei X, Boqing G, Zixia L, Lu W, Liqiang W. Improving the Improved Training of Wasserstein GANs: A Consistency Term and Its Dual Effect. International Conference on Learning Representations (ICLR 2018), Accepted as a conference paper.
Background
- Research interests include machine learning, deep learning, semi-supervised deep learning, generative adversarial networks, etc. Main research directions are artificial intelligence and big data, software engineering theory and technology, software service engineering, and key software in intelligent transportation.
Miscellany
- Personal interests and hobbies not provided.
Co-authors