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» Discrete Mixture Models for Unsupervised Image Segmentation
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ISBI
2008
IEEE
14 years 2 months ago
Unsupervised segmentation of cell nuclei using geometric models
Fluorescent microscopy of biological samples allows noninvasive screening of specific molecular events in-situ. This approach is useful for investigating intricate signalling path...
Shaun Fitch, Trevor Jackson, Peter Andras, Craig R...
ICASSP
2010
IEEE
13 years 7 months ago
Towards multi-speaker unsupervised speech pattern discovery
In this paper, we explore the use of a Gaussian posteriorgram based representation for unsupervised discovery of speech patterns. Compared with our previous work, the new approach...
Yaodong Zhang, James R. Glass
MICCAI
2008
Springer
14 years 8 months ago
MR Brain Tissue Classification Using an Edge-Preserving Spatially Variant Bayesian Mixture Model
In this paper, a spatially constrained mixture model for the segmentation of MR brain images is presented. The novelty of this work is a new, edge preserving, smoothness prior whic...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. ...
PAMI
2010
260views more  PAMI 2010»
13 years 6 months ago
Unsupervised Object Segmentation with a Hybrid Graph Model (HGM)
—In this work, we address the problem of performing class-specific unsupervised object segmentation, i.e., automatic segmentation without annotated training images. Object segmen...
Guangcan Liu, Zhouchen Lin, Yong Yu, Xiaoou Tang
ICIP
2009
IEEE
14 years 8 months ago
Modified Grabcut For Unsupervised Object Segmentation
We propose a fully automated variation of the GrabCut technique for segmenting comparatively simple images with little variation in background colour and relatively high contrast ...