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ANNPR
2006
Springer
13 years 11 months ago
Visual Classification of Images by Learning Geometric Appearances Through Boosting
We present a multiclass classification system for gray value images through boosting. The feature selection is done using the LPBoost algorithm which selects suitable features of a...
Martin Antenreiter, Christian Savu-Krohn, Peter Au...
SDM
2004
SIAM
214views Data Mining» more  SDM 2004»
13 years 8 months ago
Making Time-Series Classification More Accurate Using Learned Constraints
It has long been known that Dynamic Time Warping (DTW) is superior to Euclidean distance for classification and clustering of time series. However, until lately, most research has...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
ECCV
2006
Springer
14 years 9 months ago
TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...
BMCBI
2010
118views more  BMCBI 2010»
13 years 7 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
CVPR
2009
IEEE
15 years 2 months ago
Regularized Multi-Class Semi-Supervised Boosting
Many semi-supervised learning algorithms only deal with binary classification. Their extension to the multi-class problem is usually obtained by repeatedly solving a set of bina...
Amir Saffari, Christian Leistner, Horst Bischof