161 search results - page 17 / 33 » Image Classification using Random Forests and Ferns |
ICCV
2003
IEEE
16 years 1 months ago
2003
IEEE
We propose a two-class classification model for grouping. Human segmented natural images are used as positive examples. Negative examples of grouping are constructed by randomly m...
ECCV
2010
Springer
14 years 12 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 ...
107
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MICCAI
2008
Springer
16 years 28 days ago
2008
Springer
Locating Brain tumor segmentation within MR (magnetic resonance) images is integral to the treatment of brain cancer. This segmentation task requires classifying each voxel as eith...
119
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PRL
2000
14 years 11 months ago
2000
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
117
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Publication
One of the principal bottlenecks in applying learning techniques to classification problems is the large amount of labeled training data required. Especially for images and video, ...