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MICCAI
2005
Springer
14 years 9 months ago
MRI Tissue Classification with Neighborhood Statistics: A Nonparametric, Entropy-Minimizing Approach
We introduce a novel approach for magnetic resonance image (MRI) brain tissue classification by learning image neighborhood statistics from noisy input data using nonparametric den...
Tolga Tasdizen, Suyash P. Awate, Ross T. Whitaker,...
IJCV
2002
172views more  IJCV 2002»
13 years 8 months ago
Using Multiple-Hypothesis Disparity Maps and Image Velocity for 3-D Motion Estimation
In this paper we explore a multiple hypothesis approach to estimating rigid motion from a moving stereo rig. More precisely, we introduce the use of Gaussian mixtures to model cor...
David Demirdjian, Trevor Darrell
ECCV
2008
Springer
14 years 10 months ago
Learning Optical Flow
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
Deqing Sun, Stefan Roth, J. P. Lewis, Michael J. B...
JMLR
2010
153views more  JMLR 2010»
13 years 3 months ago
Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data
In this paper, we present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using weakly-labeled data. GE fits m...
Gideon S. Mann, Andrew McCallum
ICCV
2007
IEEE
14 years 11 months ago
Supervised Learning of Image Restoration with Convolutional Networks
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
Viren Jain, Joseph F. Murray, Fabian Roth, Sriniva...