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» Variational Bayesian image modelling
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ICPR
2008
IEEE
16 years 18 days ago
Prior-updating ensemble learning for discrete HMM
Ensemble learning is a variational Bayesian method in which an intractable distribution is approximated by a lower-bound. Ensemble learning results in models with better generaliz...
Gyeongyong Heo, Paul D. Gader
ECML
2007
Springer
16 years 10 days ago
Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
Tapani Raiko, Alexander Ilin, Juha Karhunen
ICASSP
2010
IEEE
15 years 6 months ago
An adaptive initialization method for speaker Diarization based on prosodic features
The following article presents a novel, adaptive initialization scheme that can be applied to most state-of-the-art Speaker Diarization algorithms, i.e. algorithms that use agglom...
David Imseng, Gerald Friedland
ICIP
2003
IEEE
16 years 7 months ago
Geometric segmentation of 3D structures
Segmentation in volumetric images deals with separating `objects' from their `background' in a given 3D data. Usually, one starts with `edge detectors' that give bi...
Ron Kimmel
ICPR
2004
IEEE
16 years 7 months ago
Multi-Resolution Template Kernels
Domains in which shapes of objects change rapidly and significantly are a challenge for existing representation techniques: sport is a good example of this. We present a texture-b...
Chris J. Needham, Roger D. Boyle