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JMLR
2012
13 years 8 months ago
Learning Low-order Models for Enforcing High-order Statistics
Models such as pairwise conditional random fields (CRFs) are extremely popular in computer vision and various other machine learning disciplines. However, they have limited expre...
Patrick Pletscher, Pushmeet Kohli
CVPR
2005
IEEE
16 years 8 months ago
Optimal Sub-Shape Models by Minimum Description Length
Active shape models are a powerful and widely used tool to interpret complex image data. By building models of shape variation they enable search algorithms to use a priori knowle...
Georg Langs, Philipp Peloschek, Horst Bischof
TMI
2002
143views more  TMI 2002»
15 years 5 months ago
A Support Vector Machine Approach for Detection of Microcalcifications
In this paper, we investigate an approach based on support vector machines (SVMs) for detection of microcalcification (MC) clusters in digital mammograms, and propose a successive ...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
ICCV
2011
IEEE
14 years 6 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
CVPR
2010
IEEE
16 years 2 months ago
A Steiner Tree approach to efficient object detection
We propose an approach to speeding up object detection, with an emphasis on settings where multiple object classes are being detected. Our method uses a segmentation algorithm to ...
Olga Russakovsky, Quoc Le, Andrew Ng