5 search results - page 1 / 1 » An incremental extremely random forest classifier for online... |
136
Voted
ICIP
2009
IEEE
15 years 1 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...
147
Voted
DAGM
2010
Springer
15 years 4 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...
132
Voted
ICPR
2010
IEEE
15 years 9 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...
148
Voted
PAMI
2008
15 years 3 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...
137
Voted
ECCV
2010
Springer
15 years 3 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 ...