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» A new concept of robustness
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ECCV
2004
Springer
14 years 2 months ago
Robust Fitting by Adaptive-Scale Residual Consensus
Computer vision tasks often require the robust fit of a model to some data. In a robust fit, two major steps should be taken: i) robustly estimate the parameters of a model, and ii...
Hanzi Wang, David Suter
ICCV
2001
IEEE
14 years 11 months ago
Robust Principal Component Analysis for Computer Vision
Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares...
Fernando De la Torre, Michael J. Black
TRUST
2010
Springer
14 years 2 months ago
Robust Combiners for Software Hardening
All practical software hardening schemes, as well as practical encryption schemes, e.g., AES, were not proven to be secure. One technique to enhance security is robust combiners. A...
Amir Herzberg, Haya Shulman
CDC
2009
IEEE
225views Control Systems» more  CDC 2009»
14 years 2 months ago
High performance adaptive robust control for nonlinear system with unknown input backlash
—A high performance adaptive robust control (ARC) algorithm is developed for a class of nonlinear system with unknown input backlash, parametric uncertainties and uncertain nonli...
Jian Guo, Bin Yao, Qingwei Chen, Xiaobei Wu
CVPR
2008
IEEE
14 years 11 months ago
Robust tensor factorization using R1 norm
Over the years, many tensor based algorithms, e.g. two dimensional principle component analysis (2DPCA), two dimensional singular value decomposition (2DSVD), high order SVD, have...
Heng Huang, Chris H. Q. Ding