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CVPR
2000
IEEE
13 years 11 months ago
Likelihood Functions and Confidence Bounds for Total-Least-Squares Problems
This paper addresses the derivation of likelihood functions and confidence bounds for problems involving overdetermined linear systems with noise in all measurements, often referr...
Oscar Nestares, David J. Fleet, David J. Heeger
ICIAR
2010
Springer
13 years 11 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
MICCAI
2010
Springer
13 years 6 months ago
Incorporating Priors on Expert Performance Parameters for Segmentation Validation and Label Fusion: A Maximum a Posteriori STAPL
Abstract. In order to evaluate the quality of segmentations of an image and assess intra- and inter-expert variability in segmentation performance, an Expectation Maximization (EM)...
Olivier Commowick, Simon K. Warfield
NIPS
1998
13 years 9 months ago
Probabilistic Image Sensor Fusion
We present a probabilistic method for fusion of images produced by multiple sensors. The approach is based on an image formation model in which the sensor images are noisy, locall...
Ravi K. Sharma, Todd K. Leen, Misha Pavel
SAC
2011
ACM
13 years 2 months ago
A quasi-Newton acceleration for high-dimensional optimization algorithms
Abstract In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of ...
Hua Zhou, David Alexander, Kenneth Lange