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韦佳
博士,副教授

Office: 广州大学城华南理工大学计算机科学与工程学院 B3-301
English
个人简介
      韦佳,1982年1月出生于江西省永修县,2003年和2006年在哈尔滨工业大学获工学学士和工学硕士学位,2009年在华南理工大学获工学博士学位,现为华南理工大学计算机科学与工程学院副教授,硕士生导师。主要研究兴趣包括半监督学习、表示学习、深度学习、医学图像分析等。主持国家自然科学基金项目1项,广东省自然科学基金项目2项,广东省科技计划项目1项,广州市科技计划项目1项,华南理工大学基本科研业务费项目2项。

主要期刊论文(*通讯作者)
  1. Yunjun Xiao, Jia Wei*, Jiabing Wang, Qianli Ma, Shandian Zhe, Tolga Tasdizen. Graph constraint-based robust latent space low-rank and sparse subspace clustering. Neural Computing and Applications, 2019. (https://doi.org/10.1007/s00521-019-04317-3)
  2. Meng Meng, Wei Jia*, Wang Jiabing, Ma Qianli, Wang Xuan. Adaptive Semi-Supervised Dimensionality Reduction Based on Pairwise Constraints Weighting and Graph Optimizing. International Journal of Machine Learning and Cybernetics, 8(3):793-805, 2017.
  3. Wei Jia*, Meng Meng, Wang Jiabing, Ma Qianli, Wang Xuan. Adaptive Semi-Supervised Dimensionality Reduction with Sparse Representation Using Pairwise Constraints. Neurocomputing, 177:564-571, 2016.
  4. Qi Shuhan, Wang Fanglin, Wang Xuan, Wei Jia, Zhao Hainan. Live multimedia brand-related data identification in microblog. Neurocomputing, 158: 225-233, 2015.
  5. Wei Jia*, Zeng Qunfang, Wang Xuan, Wang Jiabing, Wen Guihua. Integrating local and global topological structures for semi-supervised dimensionality reduction. Soft Computing, 18(6):1189-1198, 2014. 
  6. Cai Xianfa, Wen Guihua, Wei Jia, Li Jie, Yu Zhiwen. Perceptual relativity-based semi-supervised dimensionality reduction algorithm. Applied Soft Computing, 16:112-123, 2014. 
  7. Wen Guihua, Wei Jia, Wang Jiabing, Zhou Tiangang, Chen Lin. Cognitive gravitation model for classification on small noisy data. Neurocomputing, 118:245-252, 2013.
  8. Wen Guihua, Jiang Lijun, Wen Jun, Wei Jia, Yu Zhiwen. Perceptual realtivity-based local hyperplane classification. Neurocomputing, 97:155-163, 2012. 
  9. Yu Guoxian, Peng Hong, Wei Jia, Ma Qianli. Enhanced Locality Preserving Projections using Robust Path based Similarity. Neurocomputing, 74(4):598-605, 2011.
  10. 余国先,张国基,韦佳,任亚洲. 一种基于多图的集成直推分类方法. 电子与信息学报, 33(8):1883-1888, 2011. 
  11. 韦佳*,杨创新,马千里,余国先. 基于局部重构与全局保持的半监督判别分析方法. 华南理工大学学报(自然科学版), 38(7):45-49, 2010. 
  12. Yu Guoxian, Peng Hong, Wei Jia, Ma Qianli. Mixture Graph based Semi-Supervised Dimensionality Reduction. Pattern Recognition and Image Analysis, 20(4):536-541, 2010. 
  13. 刘利,韦佳,马千里. 基于流形学习的图像检索研究进展. 北京交通大学学报, 34(5):164-171, 2010. 
  14. Wei Jia*, Peng Hong. Neighbourhood Preserving based Semi-Supervised Dimensionality Reduction. Electronics Letters, 44(20):1190-1191, 2008. 
  15. 韦佳*,彭宏. 基于局部与全局保持的半监督维数约减方法. 软件学报, 19(11):2833-2842, 2008. 
  16. 韦佳*,彭宏,林毅申. 基于改进距离的孤立点检测方法. 华南理工大学学报(自然科学版), 36(9):25-30, 2008.


主要会议论文(*通讯作者)

  1. Wenguang Yuan, Jia Wei*, Jiabing Wang, Qianli Ma, Tolga Tasdizen. Unified Attentional Generative Adversarial Network for Brain Tumor Segmentation From Multimodal Unpaired Images. The 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), Shenzhen, China. (https://arxiv.org/abs/1907.03548)
  2. Wei Jia*, Wang Jiabing, Ma Qianli, Wang Xuan. Adaptive Semi-Supervised Dimensionality Reduction. The 2nd International Workshop on High Dimensional Data Mining (HDM) @ IEEE International Conference on Data Mining Workshop (ICDMW), 2014, 684-691.
  3. Chen Xiaochen, Wei Jia*, Li Jinhai, Zhang Xiaodong. Integrating Local and Global Manifold Structures for Unsupervised Dimensionality Reduction. The 2014 International Joint Conference on Neural Networks (IJCNN), 2014, 2837-2843.  
  4. Wang Jiabing, Zhang Pei, Wen Guihua, Wei Jia. Classifying categorical data by rule-based neighbors. The 11th IEEE International Conference on Data Mining (ICDM), 2011, 1248-1253. 
  5. Wei Jia*, Peng Hong, Lin Yishen, Huang Zhimao, Wang Jiabing. Adaptive Neighborhood Selection for Manifold Learning. The 7th International Conference on Machine Learning and Cybernetics (ICMLC), 2008, 380-384. 


专利、软件著作权

  1. 张凯文, 韦佳. 一种面向噪声图像的深度学习聚类方法, 中国, 申请号: 2019101347233. (发明专利)
  2. 袁文广, 韦佳, 张加佳. 一种用于大菠萝扑克二三轮摆法的深度增强学习方法, 中国, 申请号: 201910124932X. (发明专利)
  3. 杨秋明, 韦佳. 一种基于概率成对约束的自适应半监督降维方法, 中国, 申请号: 201810234006.3. (发明专利)
  4. 陈怀臻, 韦佳, 张加佳. 一种用于大菠萝扑克首轮摆法的卷积神经网络结构模型, 中国, 申请号: 201711204890.8. (发明专利)
  5. 韦佳, 张凯文, 陈毅贤, 陈冠宇. 两国军棋对战平台与程序AI软件V1.0, 2016.5, 中国, 2016SR095375. (计算机软件著作权)
  6. 韦佳, 吴景旺, 林涛, 陈俊伟, 金跃骄. 基于CBIR技术的宝贝搜索引擎软件V1.0, 2013.7, 中国, 2013SR076541. (计算机软件著作权)


在读硕士生

2017级:曾政文,肖云军,潘宇琳

2018级:袁文广,Nurun Nahar(欣月)

2019级:伍兆韬,陈俊晓


已毕业硕士生

杨秋明(2015-2018,@小米)

张凯文(2016-2019,@华为)


招生要求

“四好”学生:好德(小胜靠智,大胜靠德,做事必先做人),好奇(兴趣是最好的老师),好学(敏而好学,不耻下问),好动(实践是检验真理的唯一标准)


For Potential and Current Students

本、硕、博的区别,只用两组图就解释清楚了

我只希望学生能认真读研、顺利毕业

没有痛苦的博士求学经历是不合格的

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台湾清华大学教授撰写研究生手册,让你少走很多弯路!

“侯沉,你的论文充斥着垃圾”: 浅谈英文科研写作







Last updated: June 30, 2019