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Yiming Wu

Hi, I am Yiming. In Chinese, Yi means the first, and Ming means songs of birds. My first name is part of a Chinese idiom "Yi Ming Jing Ren", which means a superise success. -:)

I began my PhD study at the Computer Science Department of Florida State University in Fall 2004. My advisor is Professor Xiuwen Liu. I am also a member of Center for Applied Vision Imaging Sciences (CAVIS) at FSU. I graduated from Zhejiang University, China in June 2002, with a M.S degree. Then I worked as a research assistant at Nanyang Technological University, Singapore (Aug. 2002-Jan. 2004), where my advisor was Professor Kap Luk Chan.

I code using several langauges including C/C++, Java, MATLAB.

Research

my research area are computer vision and pattern recognition. Specifically, I focus on developing linear representation learning methods which can be used for face and other object recognition, with high recognition accuracy and low time cosuming.

Publications

Y. Wu, X. Liu and W. Mio, Learning Representations for Object Recognition using Multi-Stage Optimal Component Analysis, Neural Network, In press

Y. Wu, X. Liu, W. Mio and K. A. Gallivan, Two Stage Optimal Component Analysis via Dimensional Reduction, Computer Vision and Image Understanding (CVIU), In press.

Z. Zhang, K. Chan, Y. Wu and C. Chen, Learning a Multivariate Gaussian Mixture with the Reversible Jump MCMC Algorithm, Journal of Statistics and Computing, vol. 14, pp.343-355, 2004.

Y. Wu, X. Liu and W. Mio, Scalable Optimal Linear Representation for Face and Object Recognition, IEEE International Conference on Machine Learning and Applications, Cincinnati, OH., Dec., 2007,

Y. Wu, X. Liu and W. Mio, Multi Stage Optimal Component Analysis, International Joint Conference on Neural Network, Orlando, FL, Aug., 2007.

Y. Wu, X. Liu, W. Mio and K. A. Gallivan, Two Stage Optimal Component Analysis, International Conference on Image Processing, Atlanta, GA, Oct., 2006..

Y. Wu and K. Chan, An Extended Isomap Algorithm for Learning Multi-Class Manifold, International Conference on Machine Learning and Cybernetics, Shanghai, China, Aug., 2004..

Y. Wu, K. Chan and L. Wang, Face Recognition Based on Discriminitive Manifold Learning, IEEE International Conference on Pattern Recognition, Cambridge, UK, Aug., 2004..

Y. Wu, K. Chan and X. Yang, Color Image Segmentation Using Finite Gaussian Mixture Model, Intenational Conference on Information, Communication and Signal Processing, Singapore, Dec., 2003..

S. Tsai, Y. Wu and K. Chan, Nonlinear Dimensionality Reduction Techniques and Their Applications, In Proceeding of Nanyang Technological University Bulletin, Singapore, Sept., 2003.

Y. Wu, K. Chan and H. Wang, Texture Classification Based on Finite Gaussian Mixture Model, IEEE International workshop on Texture Analysis and Synthesis, Nice, France, Oct., 2003.

Y. Wu W. Gu and X. Ye, A Shadow handler in Traffic Monitoring System, IEEE Conference on Vehicular Technology, Birmingham, AL, May, 2002.

Y. Wu, W. Gu and X. Ye, A Method for Shadow Processing in Traffic Monitoring System, International Conference on Multimedia, Moscow, Russia, May, 2001.

Professional Services

Session chair, Dimensionality Reduction / Machine Learning in Web Based Real-Time Applications, The Sixth International Conference on Machine Learning and Applications (ICMLA'07), Cincinnati, Ohio, Dec 13-15, 2007.

IEEE Transaction on Pattern Analysis and Machine Intelligence

Journal of Statistics and Computing

Journal of Neural Computing and Applications