Ph.D.

Emaily30liu@engmail.uwaterloo.ca

Short biography

YingYing Liu received her Ph.D. degree in the field of signal and image processing at the University of Waterloo in the department of Systems Design Engineering in 2011. She received her B.E. degree from Huazhong University of Science and Technology, and her M.Sc. from Chinese Academy of Science.

Her research is primarily in image and video processing, statistical modeling and machine learning. She has published and reviewed several papers for key journals and conferences in the related areas of image processing, image analysis and pattern recognition.

Before her PhD, Ying worked for four years on the research and development of signal processing for underwater systems. In 2010, she collaborated with the compression research group in Research In Motion Ltd. on video processing research for the coming standard HEVC. Recently, she is collaborating with Center of Pattern Analysis and Machine Intelligence, University of Waterloo and working on data analysis and machine learning.

Supervisors

Paul Fieguth

Research interests

My research interests lie in multidimensional signal processing, statistical modeling, and machine learning. My work is focused on the developing methodology and application algorithms for multivariate data analysis, multiresolution representation and estimation, in particular, for image and video processing, remote sensing and scientific sensing data modeling and analysis.

Research topics

Computer Vision

Multiresolution Techniques

Remote Sensing

Scientific Imaging

Stochastic Models

Video Analysis

Research demos

Porous Media

SAR Sea Ice Image Synthesis

Publications

Journal articles 

Liu, Y.A. Wong, and P. Fieguth, "Synthesis of remote sensing label fields using a tree-structured hierarchical modelpdf",IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 6, pp. 2060-2070, 2011. Details

Conference papers

Liu, Y., D. He, and P. Fieguth, "ADAPTIVE POST-FILTERING BASED ON LOCAL BINARY PATTERNS", International Conference on Image Processing, Orlando, 2012. Details


Liu, Y.P. Fieguth, and A. Wong, "A structure-guided conditional sampling model for video resolution enhancement",IEEE International Conference on Image Processing (IEEE ICIP), 2011. Details

Liu, Y.A. Wong, and P. Fieguth, "Remote sensing image synthesispdf", 2010 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 2467 -2470, 2010. Details

Mohebi, A.Y. Liu, and P. Fieguth, "Hierarchical sampling with constraintspdf", 6th International Conference on Image Analysis and Recognition, pp. 23 - 32, 2009. Details

Liu, Y., and P. Fieguth, "Image resolution enhancement with hierarchical hidden fieldspdf", 6th International Conference on Image Analysis and Recognition, pp. 73 - 82, 2009. Details

Liu, Y., and P. Fieguth, "Parallel hidden hierarchical fields for multi-scale reconstructionpdf", 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, pp. 70–83, 2009. Details

Liu, Y.A. Mohebi, and P. Fieguth, "Modeling of multiscale porous media using multiple Markov random fields", Fourth Biot Conference on Poromechanics, New York, 2009. Details

Theses

Liu, Y., "Hidden Hierarchical Markov Fields for Image Modeling", Department of Systems Design Engineering, Waterloo, Ontario, Canada, University of Waterloo, 2011. Details

Affiliation: 
University of Waterloo

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