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ICML
2000
IEEE
14 years 2 days ago
Using Learning by Discovery to Segment Remotely Sensed Images
In this paper, we describe our research in computer-aided image analysis. We have incorporated machine learning methodologies with traditional image processing to perform unsuperv...
Leen-Kiat Soh, Costas Tsatsoulis
ICIAR
2011
Springer
12 years 11 months ago
A Texture-Based Probabilistic Approach for Lung Nodule Segmentation
Producing consistent segmentations of lung nodules in CT scans is a persistent problem of image processing algorithms. Many hard-segmentation approaches are proposed in the literat...
Olga Zinoveva, Dmitry Zinovev, Stephen A. Siena, D...
TIP
2002
179views more  TIP 2002»
13 years 7 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
CVPR
1999
IEEE
14 years 9 months ago
Histogram Clustering for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic grouping of distributional histogram data. Adopting the Bayesian framework, we propose to perform anneale...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
CVPR
2007
IEEE
14 years 9 months ago
ROI-SEG: Unsupervised Color Segmentation by Combining Differently Focused Sub Results
This paper presents a novel unsupervised color segmentation scheme named ROI-SEG, which is based on the main idea of combining a set of different sub-segmentation results. We prop...
Michael Donoser, Horst Bischof