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6 years 9 months ago
“A robust and accurate approach to blood vessel segmentation from angiography x-ray images using multi-stage random forests
In this paper we propose a novel approach based on multi-stage random forests to address problems faced by traditional vessel segmentation algorithms on account of image artifacts...
Vipin Gupta, Amit Kale and Hari Sundar
ICCV
2011
IEEE
8 years 3 months ago
Decision Tree Fields
This paper introduces a new formulation for discrete image labeling tasks, the Decision Tree Field (DTF), that combines and generalizes random forests and conditional random fiel...
Sebastian Nowozin, Carsten Rother, Shai Bagon, Ban...
PR
2011
8 years 6 months ago
Hierarchical annotation of medical images
In this paper, we describe an approach for the automatic medical annotation task of the 2008 CLEF cross-language image retrieval campaign (ImageCLEF). The data comprise 12076 full...
Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, ...
ICIC
2009
Springer
9 years 1 months ago
Towards a Better Understanding of Random Forests through the Study of Strength and Correlation
In this paper we present a study on the Random Forest (RF) family of ensemble methods. From our point of view, a "classical" RF induction process presents two main drawba...
Simon Bernard, Laurent Heutte, Sébastien Ad...
NDT
2010
9 years 2 months ago
Web Document Classification by Keywords Using Random Forests
Web directory hierarchy is critical to serve user’s search request. Creating and maintaining such directories without human experts involvement requires good classification of we...
Myungsook Klassen, Nikhila Paturi
ISCI
2007
130views more  ISCI 2007»
9 years 3 months ago
Learning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...
JMLR
2006
135views more  JMLR 2006»
9 years 3 months ago
Quantile Regression Forests
Random forests were introduced as a machine learning tool in Breiman (2001) and have since proven to be very popular and powerful for high-dimensional regression and classificatio...
Nicolai Meinshausen
JMLR
2008
198views more  JMLR 2008»
9 years 3 months ago
Consistency of Random Forests and Other Averaging Classifiers
In the last years of his life, Leo Breiman promoted random forests for use in classification. He suggested using averaging as a means The second author's research was sponso...
Gérard Biau, Luc Devroye, Gábor Lugo...
BMCBI
2010
190views more  BMCBI 2010»
9 years 3 months ago
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification alg
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...
DAGM
2010
Springer
9 years 4 months ago
On-Line Multi-view Forests for Tracking
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...
Christian Leistner, Martin Godec, Amir Saffari, Ho...
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