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» Visualizing Bagged Decision Trees
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CVPR
2008
IEEE
14 years 12 months ago
Semantic texton forests for image categorization and segmentation
We propose semantic texton forests, efficient and powerful new low-level features. These are ensembles of decision trees that act directly on image pixels, and therefore do not ne...
Jamie Shotton, Matthew Johnson, Roberto Cipolla
CEC
2009
IEEE
14 years 1 months ago
Using genetic programming to obtain implicit diversity
—When performing predictive data mining, the use of ensembles is known to increase prediction accuracy, compared to single models. To obtain this higher accuracy, ensembles shoul...
Ulf Johansson, Cecilia Sönströd, Tuve L&...
ECML
2006
Springer
14 years 1 months ago
Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions
We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...
Sébastien Jodogne, Justus H. Piater
ICIP
2005
IEEE
14 years 11 months ago
Learning to binarize document images using a decision cascade
In this article, we propose a special type of decision tree, called a decision cascade, for binarizing document images. Such images are produced by cameras, resulting in varying de...
Chien-Hsing Chou, Chih-Ching Huang, Wen-Hsiung Lin...
CVPR
2011
IEEE
13 years 5 months ago
Mining Discriminative Co-occurrence Patterns for Visual Recognition
The co-occurrence pattern, a combination of binary or local features, is more discriminative than individual features and has shown its advantages in object, scene, and action rec...
Junsong Yuan, Ming Yang, Ying Wu