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» Meta-Evaluation of Image Segmentation Using Machine Learning
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CVPR
2010
IEEE
13 years 7 months ago
Modeling pixel means and covariances using factorized third-order boltzmann machines
Learning a generative model of natural images is a useful way of extracting features that capture interesting regularities. Previous work on learning such models has focused on me...
Marc Aurelio Ranzato, Geoffrey E. Hinton
ICCV
2003
IEEE
14 years 9 months ago
Machine Learning and Multiscale Methods in the Identification of Bivalve Larvae
This paper describes a novel application of support vector machines and multiscale texture and color invariants to a problem in biological oceanography: the identification of 6 sp...
Sanjay Tiwari, Scott Gallager
CVPR
2008
IEEE
14 years 9 months ago
Recognition by association via learning per-exemplar distances
We pose the recognition problem as data association. In this setting, a novel object is explained solely in terms of a small set of exemplar objects to which it is visually simila...
Tomasz Malisiewicz, Alexei A. Efros
ICPR
2004
IEEE
14 years 8 months ago
A Variational Approach for Color Image Segmentation
In this paper we use a variational Bayesian framework for color image segmentation. Each image is represented in the L*u*v color coordinate system before being segmented by the va...
Nikolaos Nasios, Adrian G. Bors
TVCG
2010
183views more  TVCG 2010»
13 years 5 months ago
Exploration and Visualization of Segmentation Uncertainty using Shape and Appearance Prior Information
—We develop an interactive analysis and visualization tool for probabilistic segmentation in medical imaging. The originality of our approach is that the data exploration is guid...
Ahmed Saad, Ghassan Hamarneh, Torsten Möller