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ECCV
2006
Springer
14 years 9 months ago
Learning to Combine Bottom-Up and Top-Down Segmentation
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
Anat Levin, Yair Weiss
CVPR
2010
IEEE
13 years 10 months ago
Co-clustering of Image Segments Using Convex Optimization Applied to EM Neuronal Reconstruction
This paper addresses the problem of jointly clustering two segmentations of closely correlated images. We focus in particular on the application of reconstructing neuronal structu...
Shiv Vitaladevuni, Ronen Basri
ISBI
2011
IEEE
12 years 11 months ago
Automatic pancreas segmentation in contrast enhanced CT data using learned spatial anatomy and texture descriptors
Pancreas segmentation in 3-D computed tomography (CT) data is of high clinical relevance, but extremely difficult since the pancreas is often not visibly distinguishable from the...
Marius Erdt, Matthias Kirschner, Klaus Drechsler, ...
ICIP
2007
IEEE
14 years 2 months ago
Modeling vs. Segmenting Images Using A Probabilistic Approach
Image segmentation is conventionally formulated as a pixellabeling problem, in which “hard” decisions have to be made to partition pixels into regions. As image segmentation i...
Datong Chen
BMVC
2010
13 years 2 months ago
Saliency Segmentation based on Learning and Graph Cut Refinement
Saliency detection is a well researched problem in computer vision. In previous work, most of the effort is spent on manually devising a saliency measure. Instead we propose a sim...
Paria Mehrani, Olga Veksler