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AAAI
2008
13 years 11 months ago
Unsupervised Categorization (Filtering) of Google Images Based on Visual Consistency
The objective of this paper is to study the existing methods for unsupervised object recognition and image categorization and propose a model that can learn directly from the outp...
Pooyan Fazli, Ara Bedrosian
ECML
2006
Springer
14 years 13 days ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
CVPR
2004
IEEE
14 years 10 months ago
Is Bottom-Up Attention Useful for Object Recognition?
A key problem in learning multiple objects from unlabeled images is that it is a priori impossible to tell which part of the image corresponds to each individual object, and which...
Ueli Rutishauser, Dirk Walther, Christof Koch, Pie...
CVPR
2005
IEEE
14 years 10 months ago
Joint Nonparametric Alignment for Analyzing Spatial Gene Expression Patterns in Drosophila Imaginal Discs
To compare spatial patterns of gene expression, one must analyze a large number of images as current methods are only able to measure a small number of genes at a time. Bringing i...
Parvez Ahammad, Cyrus L. Harmon, Ann Hammonds, Sha...
ICCV
2009
IEEE
1198views Computer Vision» more  ICCV 2009»
15 years 1 months ago
Implicit Color Segmentation Features for Pedestrian Detection
We investigate the problem of pedestrian detection in still images. Sliding window classifiers, notably using the Histogram-of-Gradient (HOG) features proposed by Dalal and Trig...
Patrick Ott and Mark Everingham