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ICCV
2007
IEEE
15 years 4 days ago
Active Learning with Gaussian Processes for Object Categorization
Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate of uncertainty. Gauss...
Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Tr...
MICCAI
2009
Springer
14 years 11 months ago
A Generic Probabilistic Active Shape Model for Organ Segmentation
Probabilistic models are extensively used in medical image segmentation. Most of them employ parametric representations of densities and make idealizing assumptions, e.g. normal di...
Andreas Wimmer, Grzegorz Soza, Joachim Hornegger
ICML
2005
IEEE
14 years 11 months ago
Active learning for sampling in time-series experiments with application to gene expression analysis
Many time-series experiments seek to estimate some signal as a continuous function of time. In this paper, we address the sampling problem for such experiments: determining which ...
Rohit Singh, Nathan Palmer, David K. Gifford, Bonn...
CORR
2008
Springer
100views Education» more  CORR 2008»
13 years 10 months ago
Statistical region-based active contours with exponential family observations
In this paper, we focus on statistical region-based active contour models where image features (e.g. intensity) are random variables whose distribution belongs to some parametric ...
François Lecellier, Stéphanie Jehan-...
TCS
2010
13 years 8 months ago
Active learning in heteroscedastic noise
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
András Antos, Varun Grover, Csaba Szepesv&a...