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» Nearest Neighbor Distributions and Noise Variance Estimation
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JMLR
2010
128views more  JMLR 2010»
13 years 3 months ago
On the Rate of Convergence of the Bagged Nearest Neighbor Estimate
Bagging is a simple way to combine estimates in order to improve their performance. This method, suggested by Breiman in 1996, proceeds by resampling from the original data set, c...
Gérard Biau, Frédéric C&eacut...
ECCV
2008
Springer
13 years 6 months ago
Estimating Radiometric Response Functions from Image Noise Variance
We propose a method for estimating radiometric response functions from observation of image noise variance, not profile of its distribution. The relationship between radiance inten...
Jun Takamatsu, Yasuyuki Matsushita, Katsushi Ikeuc...
ICIAR
2010
Springer
13 years 8 months ago
Segmentation Based Noise Variance Estimation from Background MRI Data
Accurate and precise estimation of the noise variance is often of key importance as an input parameter for posterior image processing tasks. In MR images, background data is well s...
Jeny Rajan, Dirk Poot, Jaber Juntu, Jan Sijbers
JSAC
2008
85views more  JSAC 2008»
13 years 4 months ago
A distributed minimum variance estimator for sensor networks
A distributed estimation algorithm for sensor networks is proposed. A noisy time-varying signal is jointly tracked by a network of sensor nodes, in which each node computes its es...
Alberto Speranzon, Carlo Fischione, Karl Henrik Jo...
ICCV
2007
IEEE
14 years 6 months ago
High-Dimensional Feature Matching: Employing the Concept of Meaningful Nearest Neighbors
Matching of high-dimensional features using nearest neighbors search is an important part of image matching methods which are based on local invariant features. In this work we hi...
Dusan Omercevic, Ondrej Drbohlav, Ales Leonardis