19 search results - page 4 / 4 » Learning from data with uncertain labels by boosting credal ... |
ECCV
2008
Springer
14 years 11 months ago
2008
Springer
Abstract. Object detection is one of the key problems in computer vision. In the last decade, discriminative learning approaches have proven effective in detecting rigid objects, a...
DAGM
2010
Springer
13 years 11 months ago
2010
Springer
Abstract. A successful approach to tracking is to on-line learn discriminative classifiers for the target objects. Although these trackingby-detection approaches are usually fast a...
TSP
2010
13 years 4 months ago
2010
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
ECCV
2010
Springer
13 years 10 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 ...