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» Improved Segmentation Based on Probabilistic Labeling
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BIOCOMP
2008
13 years 4 months ago
Improved Segmentation Based on Probabilistic Labeling
⎯This paper presents an improved multi-object segmentation algorithm based on probabilistic labeling. First, a critical look is focused on utilizing vector calculus operator and ...
Kai-Chieh Yang, Ming-Chi Jhuang, Chun-Shun Tseng, ...
TMI
2010
217views more  TMI 2010»
12 years 10 months ago
A Generative Model for Image Segmentation Based on Label Fusion
We propose a nonparametric, probabilistic model for the automatic segmentation of medical images, given a training set of images and corresponding label maps. The resulting inferen...
Mert R. Sabuncu, B. T. Thomas Yeo, Koenraad Van Le...
3DOR
2008
13 years 6 months ago
Markov Random Fields for Improving 3D Mesh Analysis and Segmentation
Mesh analysis and clustering have became important issues in order to improve the efficiency of common processing operations like compression, watermarking or simplification. In t...
Guillaume Lavoué, Christian Wolf
ECCV
2010
Springer
13 years 6 months ago
Learning Shape Segmentation Using Constrained Spectral Clustering and Probabilistic Label Transfer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
ICML
2001
IEEE
14 years 4 months ago
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...