221 search results - page 16 / 45 » Learning from Labeled and Unlabeled Data Using Random Walks |
ICPR
2002
IEEE
14 years 9 months ago
2002
IEEE
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
ICCV
2011
IEEE
12 years 8 months ago
2011
IEEE
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
ICCV
2007
IEEE
14 years 9 months ago
2007
IEEE
Many computer vision tasks may be expressed as the problem of learning a mapping between image space and a parameter space. For example, in human body pose estimation, recent rese...
ICMCS
2005
IEEE
14 years 1 months ago
2005
IEEE
Training a good text detector requires a large amount of labeled data, which can be very expensive to obtain. Cotraining has been shown to be a powerful semi-supervised learning t...
ICCV
2003
IEEE
14 years 9 months ago
2003
IEEE
Labeling video data is an essential prerequisite for many vision applications that depend on training data, such as visual information retrieval, object recognition, and human act...