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» Discrete Mixture Models for Unsupervised Image Segmentation
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ISBI
2008
IEEE
15 years 3 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
14 years 9 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
15 years 10 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»
14 years 8 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
15 years 10 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 ...