姓 名: |
魏翔 |
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职 务: |
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职 称: |
副教授 |
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学 历: |
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学 位: |
博士 |
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通信地址: |
逸夫楼西702 |
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邮 编: |
100044 |
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办公电话: |
(010)51687354 |
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电子邮箱: |
博士(硕博连读),2012.9-2019.01,北京交通大学,软件工程,导师:卢苇 联合培养,2016.12-2017.12,美国中佛罗里达大学,图像处理与深度学习 学士,2008.9-2012.6,天津工业大学,计算机科学与技术
主要研究方向为:机器学习,深度学习、半监督深度学习、生成对抗神经网络等 |
2019.1~至今 北京交通大学,软件学院,讲师 |
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本科生课程:《计算机组成原理》 研究生课程:《机器学习》《深度学习与强化学习》 |
[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 1区) [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. https://github.com/xyk0058/FGBC. (SCI 1区) [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, 获Seeing Through the Rain (STRAIN): Vision Task Challenges in Real-world Rain Scenes in ICME 2023 Grand Challenges第1名) [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 1区)
[6]. Wei Xiang, WANG Jing-Jie, ZHANG Shun-Li, ZHANG Di, ZHANG Jian, WEI Xiao-Tao. ReLSL:基于可靠标签选择与学习的半监督学习算法[J]. 计算机学报,2022. (CCF-A) [7]. X. Wei, X. Wei, X. Kong, S. Lu, W. Xing, W. Lu, FMixCutMatch for semi-supervised deep learning. Neural Networks. https://doi.org/10.1016/j.neunet.2020.10.018. (2020). (SCI 1区) [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. [12]. Siyang Lu, Xiang Wei, Yandong Li, and Liqiang Wang. Anomaly Detection from Big Data System Logs Using Convolutional Neural Network. In 2018 IEEE Cyber Science and Technology Congress (CyberSciTech). Athens, Greece. August 12-15, 2018. [13]. Wei X, Lu W, Xing W. Learning Motion Rules from Real Data: Neural Network for Crowd Simulation[J]. Neurocomputing, 2018, 310: 125-134. [14]. Wei X, Lu W, Bao P, et al. MGA for feature weight learning in SVM—a novel optimization method in pedestrian detection[J]. Multimedia Tools and Applications, 2018, 77(7): 9021-9037. [15]. Lu W, Wei X*, Xing W, et al. Trajectory-based motion pattern analysis of crowds[J]. Neurocomputing, 2017, 247: 213-223. [16]. Wei X, Lu W, Xing W. A rapid multi-source shortest path algorithm for interactive image segmentation[J]. Multimedia Tools and Applications, 2017, 76(20): 21547-21563. [17]. Xing W, Wei X, Zhang J, Ren C, Lu W. Hybrid motion graph for character motion synthesis[J]. Journal of Visual Languages & Computing, 2014, 25(1): 20-32. [18]. Xing W, Wei X, Lu W. Weighted time-based global hierarchical path planning in dynamic environment[J]. Transactions of Tianjin University, 2014, 20(3): 223-231. |
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[1]. 中国专利,邢薇薇,魏翔,卢苇,刘渭滨,动态时变环境下寻求全局时间最优路径的方法,授权,2014.5.23,ZL201410222902.X [2]. 中国专利,魏翔,卢苇,邢薇薇,杨宇翔,张顺利,一种基于多源路径最短距离的交互式图像分割方法,申请,2016.11.21,201611039325.6 [3]. 中国专利,邢薇薇,魏翔,卢苇,杨宇翔,张顺利,一种基于支持向量机的行人检测方法及系统,申请,2016.12.26,201611221282.3 |