221 search results - page 33 / 45 » Learning from Labeled and Unlabeled Data Using Random Walks |
ISBI
2008
IEEE
14 years 8 months ago
2008
IEEE
In this paper, we examine the use of implicit shape representations for nonrigid registration of serial CT liver examinations. Using ground truth in the form of corresponding land...
ECCV
2010
Springer
13 years 8 months ago
2010
Springer
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
SLSFS
2005
Springer
14 years 1 months ago
2005
Springer
We propose the use of latent space models applied to local invariant features for object classification. We investigate whether using latent space models enables to learn patterns...
PCM
2007
Springer
14 years 2 months ago
2007
Springer
A novel method for creating diverse ensembles of image classifiers is proposed. The idea is that, for each base image classifier in the ensemble, a random image transformation is g...
EMNLP
2004
13 years 9 months ago
2004
Active learning (AL) promises to reduce the cost of annotating labeled datasets for trainable human language technologies. Contrary to expectations, when creating labeled training...