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» Simplifying mixture models through function approximation
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VISUALIZATION
1997
IEEE
13 years 11 months ago
Simplifying polygonal models using successive mappings
: We present the use of mapping functions to automatically generate levels of detail with known error bounds for polygonal models. We develop a piece-wise linear mapping function f...
Jonathan D. Cohen, Dinesh Manocha, Marc Olano
MICCAI
2008
Springer
14 years 8 months ago
Discovering Modes of an Image Population through Mixture Modeling
Abstract. We present iCluster, a fast and efficient algorithm that clusters a set of images while co-registering them using a parameterized, nonlinear transformation model. The out...
Mert R. Sabuncu, Serdar K. Balci, Polina Golland
ICASSP
2011
IEEE
12 years 11 months ago
Gaussian mixture modeling for source localization
Exploiting prior knowledge, we use Bayesian estimation to localize a source heard by a fixed sensor network. The method has two main aspects: Firstly, the probability density fun...
John T. Flåm, Joakim Jalden, Saikat Chatterj...
ISBI
2009
IEEE
14 years 2 months ago
Image-Driven Population Analysis Through Mixture Modeling
—We present iCluster, a fast and efficient algorithm that clusters a set of images while co-registering them using a parameterized, nonlinear transformation model. The output of...
Mert R. Sabuncu
ICIP
2000
IEEE
14 years 9 months ago
Cancellation of Show-Through in Duplex Scanning
When scanning a page with printing on both sides, the printing on the back-side often shows through in the scan of the front-side because the page is not completely opaque. This p...
Gaurav Sharma