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» Non-parametric Mixture Models for Clustering
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ICDAR
2009
IEEE
15 years 6 months ago
Unsupervised Selection and Discriminative Estimation of Orthogonal Gaussian Mixture Models for Handwritten Digit Recognition
The problem of determining the appropriate number of components is important in finite mixture modeling for pattern classification. This paper considers the application of an unsu...
Xuefeng Chen, Xiabi Liu, Yunde Jia
ICTAI
2010
IEEE
14 years 9 months ago
Unsupervised Greedy Learning of Finite Mixture Models
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
ICIAR
2010
Springer
14 years 9 months ago
Image Segmentation for Robots: Fast Self-adapting Gaussian Mixture Model
Image segmentation is a critical low-level visual routine for robot perception. However, most image segmentation approaches are still too slow to allow real-time robot operation. I...
Nicola Greggio, Alexandre Bernardino, José ...
ICASSP
2009
IEEE
14 years 9 months ago
Blind sparse source separation for unknown number of sources using Gaussian mixture model fitting with Dirichlet prior
In this paper, we propose a novel sparse source separation method that can be applied even if the number of sources is unknown. Recently, many sparse source separation approaches ...
Shoko Araki, Tomohiro Nakatani, Hiroshi Sawada, Sh...
GFKL
2007
Springer
148views Data Mining» more  GFKL 2007»
15 years 6 months ago
Mixture Model Based Group Inference in Fused Genotype and Phenotype Data
The analysis of genetic diseases has classically been directed towards establishing direct links between cause, a genetic variation, and effect, the observable deviation of phenot...
Benjamin Georgi, M. Anne Spence, Pamela Flodman, A...