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» Segmentation of Mammosphere Structures from Volumetric Data
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NIPS
2004
13 years 8 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
SIGMOD
2008
ACM
158views Database» more  SIGMOD 2008»
14 years 7 months ago
Sampling cube: a framework for statistical olap over sampling data
Sampling is a popular method of data collection when it is impossible or too costly to reach the entire population. For example, television show ratings in the United States are g...
Xiaolei Li, Jiawei Han, Zhijun Yin, Jae-Gil Lee, Y...
CAIP
2009
Springer
209views Image Analysis» more  CAIP 2009»
14 years 13 hour ago
Total Variation Processing of Images with Poisson Statistics
This paper deals with denoising of density images with bad Poisson statistics (low count rates), where the reconstruction of the major structures seems the only reasonable task. Ob...
Alex Sawatzky, Christoph Brune, Jahn Müller, ...
CVPR
2010
IEEE
14 years 2 months ago
Motion Estimation with Non-Local Total Variation Regularization
State-of-the-art motion estimation algorithms suffer from three major problems: Poorly textured regions, occlusions and small scale image structures. Based on the Gestalt principle...
Manuel Werlberger, Thomas Pock, Horst Bischof
CGF
2008
148views more  CGF 2008»
13 years 7 months ago
Automatic Registration for Articulated Shapes
We present an unsupervised algorithm for aligning a pair of shapes in the presence of significant articulated motion and missing data, while assuming no knowledge of a template, u...
Will Chang, Matthias Zwicker