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» Advances in Mixture Models
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MCS
2005
Springer
16 years 9 days ago
A Probability Model for Combining Ranks
Mixed Group Ranks is a parametric method for combining rank based classiers that is eective for many-class problems. Its parametric structure combines qualities of voting methods...
Ofer Melnik, Yehuda Vardi, Cun-Hui Zhang
ICCV
1999
IEEE
16 years 8 months ago
Segmentation using Eigenvectors: A Unifying View
Automatic grouping and segmentation of images remains a challenging problem in computer vision. Recently, a number of authors have demonstrated good performance on this task using...
Yair Weiss
ECCV
2000
Springer
16 years 8 months ago
Coupled Geodesic Active Regions for Image Segmentation: A Level Set Approach
Abstract. This paper presents anovel variational method forimage segmentation that uni es boundary and region-based information sources under the Geodesic Active Region framework. ...
Nikos Paragios, Rachid Deriche
ICIP
2007
IEEE
16 years 8 months ago
Color Image Superresolution Based on a Stochastic Combinational Classification-Regression Algorithm
Abstract - The proposed algorithm in this work provides superresolution for color images by using a learning based technique that utilizes both generative and discriminant approach...
Karl S. Ni, Truong Q. Nguyen
ICIP
2007
IEEE
16 years 8 months ago
A Statistical Approach for Intensity Loss Compensation of Confocal Microscopy Images
In this paper a probabilistic technique for compensation of intensity loss in the confocal microscopy images is presented. Confocal microscopy images are modeled as a mixture of t...
Sowmya Gopinath, Ninad Thakoor, Jean Gao, Kate Lub...