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» Simplifying mixture models through function approximation
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VISUALIZATION
1997
IEEE
15 years 5 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
105
Voted
MICCAI
2008
Springer
16 years 2 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
128
Voted
ICASSP
2011
IEEE
14 years 4 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...
135
Voted
ISBI
2009
IEEE
15 years 8 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
100
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ICIP
2000
IEEE
16 years 2 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