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ECCV
2006
Springer
14 years 11 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
ICDAR
2009
IEEE
14 years 4 months ago
Raster Map Image Analysis
Raster map images (e.g., USGS) provide much information in digital form; however, the color assignments and pixel labels leave many serious ambiguities. A color histogram classi...
Thomas C. Henderson, Trevor Linton
ICIAR
2010
Springer
13 years 7 months ago
Image Segmentation for Robots: Fast Self-adapting Gaussian Mixture Model
Image segmentation is a critical low-level visual routine for robot perception. However, most image segmentation approaches are still too slow to allow real-time robot operation. I...
Nicola Greggio, Alexandre Bernardino, José ...
ISBI
2011
IEEE
13 years 1 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, ...
IJON
2010
189views more  IJON 2010»
13 years 8 months ago
Inference and parameter estimation on hierarchical belief networks for image segmentation
We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains...
Christian Wolf, Gérald Gavin