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米建勋
2015年12月15日 16:32 来源: 作者:   阅读次 上传:管理员 组别:管理组
  
 

米建勋(Mi Jian-Xun)

博士/博士后

副教授,硕士生导师

重庆邮电大学

计算机科学与技术学院 计算机系

联系方式:

工作地址:信息科学楼18楼1811

招收硕士研究生,人工智能,模式识别方向

招收本科研究助理

博士学位:

2004.9-2011.1在中国科学技术大学攻读并获得博士学位,期间在伦敦大学学院(University College London做国家公派访问研究生。

·专业:模式识别与智能系统

学士学位:

2000.9-2004.7在四川大学自动化系读本科,获得学士学位。保送中科大攻读研究生

2011.7-2013.9在哈尔滨工业大学(深圳研究生院),计算机科学与技术学院,做博士后研究工作。

2013年9月至今,在重庆邮电大学,计算机科学与技术学院,任教。

主要研究领域:

人工智能、 模式识别、 智能计算

1. Jian-Xun Mi and De-Shuang Huang, “Image compression using principal component neural network,” The 8th International Conference on Control, Automation, Robotics and Vision (ICARCV2004), pp.698-701,2004(SCI)

2. De-Shuang Huang and Jian-Xun Mi, "A new constrained independent component analysis method," IEEE Transactions on Neural networks, Volume 18,Issue 5,Sept. 2007 Page(s):1532 – 1535 (SCI)

3. Jian-Xun Mi and Jie Gui, “A method for ICA with reference signals” The 6th International Conference on Intelligent Computing, Aug. 2010 ,LNCS Volume 6216.pp.156-162 (EI)

4. Jian-Xun Mi, "A New Subspace Approach for Face Recognition”. The 7th International Conference on Intelligent Computing, 2011, Bio-Inspired Computing and Applications. vol. 6840, 2012, pp. 551-557. (EI)

5. Jian-Xun Mi, J.-X. Liu, and J. Wen, "New Robust Face Recognition Methods Based on Linear Regression," Plos One, vol. 7, p. e42461, 2012(SCI)

6. Jian-Xun Mi and Y. Yang, "A Comparative Study of Two Independent Component Analysis Using Reference Signal Methods," in Emerging Intelligent Computing Technology and Applications. vol. 304, D.-S. Huang, P. Gupta, X. Zhang, and P. Premaratne, Eds., ed: Springer Berlin Heidelberg, 2012, pp. 93-99. (EI)

7. C. H. Zheng, J.-X. Liu, Jian-Xun Mi, and Y. Xu, "Identifying Characteristic Genes Based on Robust Principal Component Analysis Emerging Intelligent Computing Technology and Applications." vol. 304, D.-S. Huang, P. Gupta, X. Zhang, and P. Premaratne, Eds., ed: Springer Berlin Heidelberg, 2012, pp. 174-179. (EI)

8. Jian-Xun Mi, "Face image recognition via collaborative representation on selected training samples," Optik - International Journal for Light and Electron Optics (DOI: 10.1016/j.ijleo.2012.10.051) (SCI)

9.Jian-Xun Mi, De-Shuang Huang, Bing, Wang, Xingjie Zhu“The Nearest-farthest Subspace Classification for Face Recognition.” Neurocomputing, vol. 113, pp. 241-250, 2013. (DOI: 10.1016/j.neucom.2013.01.003) (SCI)

10. Jian-Xun Mi, J.-X. Liu, “Face Recognition Using Sparse Representation-Based Classification on K-Nearest Subspace”, PLoS ONE 8(3): e59430. doi:10.1371/journal.pone.0059430 (SCI)

11. Jian-Xun Mi and Y. Xu, "A comparative study and improvement of two ICA using reference signal methods," Neurocomputing, vol. 137, pp. 157-164, Aug 2014.

12. Y. Zhao, H. He, and Jian-Xun Mi, "Noisy component extraction with reference," Frontiers of Computer Science, pp. 1-10, 2013/01/01 2013 (DOI:10.1007/s11704-013-1135-5). (SCI)

13. J. Wen, J. Cui, Z. Lai, and Jian-Xun Mi, "A Competitive Sample Selection Method for Palmprint Recognition," in Intelligent Science and Intelligent Data Engineering. vol. 7751, J. Yang, F. Fang, and C. Sun, Eds., ed: Springer Berlin Heidelberg, 2013, pp. 158-164. (EI)

14. Yong Xu, Qi Zhua, Zizhu Fan, David Zhang, Jian-Xun Mi, Zhihui Lai, “Using the idea of the sparse representation to perform coarse to fine face recognition’, Information Sciences, Information Sciences, vol. 238, pp. 138-148, 2013. ( DOI: 10.1016/j.ins.2013.02.051) (SCI,)

15. Jiajun Wen, Yan Chen, Jian-Xun Mi, “A palmprint recognition method based on multi-step representation”, Optik (Accepted) (SCI)

16. J.-X. Liu, Y.-T. Wang, C.-H. Zheng, W. Sha, Jian-Xun Mi, and Y. Xu, "Robust PCA based method for discovering differentially expressed genes," BMC Bioinformatics, vol. 14, p. S3, 2013. (SCI)

17. Jian-Xun Mi, D. Lei, and J. Gui, "A novel method for recognizing face with partial occlusion via sparse representation," Optik - International Journal for Light and Electron Optics, vol. 124, pp. 6786-6789, 12, 2013.(SCI)

18. Jian-Xun Mi, "A Novel Algorithm for Independent Component Analysis with Reference and Methods for Its Applications,"PLoS ONE, vol. 9, p. e93984, May 14, 2014.

19. J.-X. Liu, J. Liu, Y.-L. Gao, Jian-Xun Mi, C.-X. Ma, and D. Wang, "A Class-Information-Based Penalized Matrix Decomposition for Identifying Plants Core Genes Responding to Abiotic Stresses," PLoS ONE, vol. 9, p. e106097, 2014. (SCI)

研究项目

1.“基于表达残差稀疏性的遮挡人脸识别方法研究“ 国家自然基金项目(青年)22万元人民币(项目编号61202276),2013年1月至2015年12月 (项目主持人)

2.基于线性表达模型的人脸识别方法研究” 中国博士后科学基金第53批面上资助 (项目主持人)

3.“一种基于误差纠正的人脸识别方法研究” 重庆邮电大学青年科学研究项目(项目主持人)

4.一种基于纠错解码的人脸识别方法”重庆市基础与前沿研究计划一般项目(项目主持人,立项编号:cstc2014jcyjA40018)2014-07-01 至2017-06-30

5.“面向复杂环境下的鲁棒人脸识别研究” 重庆市教委科学技术研究项目(项目主持人,立项编号:)2015年07月 至2017年6月

专利

“一种人脸识别的方法及设置“ 发明专利,申请号201410088003.5,申请日期2014年03月11日