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» Image Classification using Random Forests and Ferns
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BMCBI
2010
190views more  BMCBI 2010»
14 years 11 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...
CVPR
2009
IEEE
16 years 7 months ago
Class-Specific Hough Forests for Object Detection
We present a method for the detection of instances of an object class, such as cars or pedestrians, in natural images. Similarly to some previous works, this is accomplished via ...
Juergen Gall, Victor S. Lempitsky
FUIN
2010
268views more  FUIN 2010»
14 years 6 months ago
Boruta - A System for Feature Selection
Machine learning methods are often used to classify objects described by hundreds of attributes; in many applications of this kind a great fraction of attributes may be totally irr...
Miron B. Kursa, Aleksander Jankowski, Witold R. Ru...
CVPR
2008
IEEE
16 years 1 months ago
Selective hidden random fields: Exploiting domain-specific saliency for event classification
Classifying an event captured in an image is useful for understanding the contents of the image. The captured event provides context to refine models for the presence and appearan...
Vidit Jain, Amit Singhal, Jiebo Luo
CVPR
2007
IEEE
16 years 1 months ago
Incorporating On-demand Stereo for Real Time Recognition
A new method for localising and recognising hand poses and objects in real-time is presented. This problem is important in vision-driven applications where it is natural for a use...
Thomas Deselaers, Antonio Criminisi, John M. Winn,...