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» Learning Statistical Structure for Object Detection
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CVPR
2006
IEEE
14 years 9 months ago
A Design Principle for Coarse-to-Fine Classification
Coarse-to-fine classification is an efficient way of organizing object recognition in order to accommodate a large number of possible hypotheses and to systematically exploit shar...
Sachin Gangaputra, Donald Geman
ICASSP
2011
IEEE
12 years 11 months ago
Occlusion-based depth ordering on monocular images with Binary Partition Tree
This paper proposes a system to relate objects in an image using occlusion cues and arrange them according to depth. The system does not rely on any a priori knowledge of the scen...
Guillem Palou, Philippe Salembier
JMLR
2008
168views more  JMLR 2008»
13 years 7 months ago
Max-margin Classification of Data with Absent Features
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbe...
BMCBI
2010
97views more  BMCBI 2010»
13 years 7 months ago
Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on es...
Dirk Repsilber, Sabine Kern, Anna Telaar, Gerhard ...
ICCV
2003
IEEE
14 years 23 days ago
Modeling Textured Motion : Particle, Wave and Sketch
In this paper, we present a generative model for textured motion phenomena, such as falling snow, wavy river and dancing grass, etc. Firstly, we represent an image as a linear sup...
Yizhou Wang, Song Chun Zhu