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Name:
Zhou Xiang-Dong
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Doctor
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No.266 Fangzheng Avenue,Shuitu Hi-tech Industrial Park, Shuitu Town, Beibei District, Chongqing
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  Research Interests: Handwriting Recognition, Document Analysis, Face Recognition and Deep Learning

  Xiang-Dong Zhou is an associate professor at the Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences. He received the B.S. degree in Applied Mathematics, the M.S. degree in Management Science and Engineering from National University of Defense Technology, Changsha, China, the Ph.D. degree in pattern recognition and artificial intelligence from the Institute of Automation, Chinese Academy of Sciences, Beijing, China, in 1998, 2003 and 2009, respectively. He was a postdoctoral fellow at Tokyo University of Agriculture and Technology from March 2009 to March 2011. From May 2011 to October 2013, he was a research assistant and later an associate professor at the Institute of Software, Chinese Academy of Sciences. His research interests include handwriting recognition, document analysis, face recognition and deep learning.

  Publication:
  X.D. Zhou, D.H. Wang, C.L. Liu, A robust approach to text line grouping in online handwritten Japanese documents, Pattern Recognition 42 (9) (2009), 2077-2088.
  X.D. Zhou, D.H. Wang, F. Tian, C.L. Liu, M. Nakagawa, Handwritten Chinese/Japanese text recognition using semi-Markov conditional random fields, IEEE Trans. Pattern Anal. Mach. Intell. 35 (10) (2013), 2413-2426.
  X.D. Zhou, Y.M. Zhang, F. Tian, H.A. Wang, C.L. Liu, Minimum-risk training for semi-Markov conditional random fields with application to handwritten Chinese/Japanese text recognition, Pattern Recognition 47 (5) (2014), 1904-1916.
  D.H. Wang, C.L. Liu, X.D. Zhou, An approach for real-time recognition of online Chinese handwritten sentences, Pattern Recognition 45 (10) (2012), 3661-3675.
  X.D. Zhou, F. Yin, D.H. Wang, Q.F. Wang, C.L. Liu, M. Nakagawa, Transcript mapping for handwritten text lines using conditional random fields, Proceedings of the 11th International Conference on Document Analysis and Recognition, Beijing, China, 2011, pp. 58-62.


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