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ICML
2008
IEEE
14 years 8 months ago
Extracting and composing robust features with denoising autoencoders
Previous work has shown that the difficulties in learning deep generative or discriminative models can be overcome by an initial unsupervised learning step that maps inputs to use...
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pi...
ICIAR
2009
Springer
13 years 5 months ago
A Robust Modular Wavelet Network Based Symbol Classifier
This paper presents a robust automatic shape classifier using modular wavelet networks (MWNs). A shape descriptor is constructed based on a combination of global geometric features...
Akshaya Kumar Mishra, Paul W. Fieguth, David A. Cl...
CRV
2011
IEEE
254views Robotics» more  CRV 2011»
12 years 7 months ago
Wavelet Model-based Stereo for Fast, Robust Face Reconstruction
—When reconstructing a specific type or class of object using stereo, we can leverage prior knowledge of the shape of that type of object. A popular class of object to reconstru...
Alan Brunton, Jochen Lang, Eric Dubois, Chang Shu
COLT
2001
Springer
14 years 3 days ago
Robust Learning - Rich and Poor
A class C of recursive functions is called robustly learnable in the sense I (where I is any success criterion of learning) if not only C itself but even all transformed classes ...
John Case, Sanjay Jain, Frank Stephan, Rolf Wiehag...
ICCV
2009
IEEE
13 years 5 months ago
A robust boosting tracker with minimum error bound in a co-training framework
The varying object appearance and unlabeled data from new frames are always the challenging problem in object tracking. Recently machine learning methods are widely applied to tra...
Rong Liu, Jian Cheng, Hanqing Lu