5 search results - page 1 / 1 » An incremental extremely random forest classifier for online... |
ICIP
2009
IEEE
13 years 2 months ago
2009
IEEE
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
DAGM
2010
Springer
13 years 5 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...
ICPR
2010
IEEE
13 years 10 months ago
2010
IEEE
—Randomized learning methods (i.e., Forests or Ferns) have shown excellent capabilities for various computer vision applications. However, it was shown that the tree structure in...
PAMI
2008
13 years 4 months ago
2008
This paper introduces three new contributions to the problems of image classification and image search. First, we propose a new image patch quantization algorithm. Other competitiv...
ECCV
2010
Springer
13 years 4 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 ...