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DAGM
1998
Springer
15 years 4 months ago
Discrete Mixture Models for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic clustering of histogram data and, more generally, for the analysis of discrete co occurrence data. Adoptin...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
MVA
2000
122views Computer Vision» more  MVA 2000»
15 years 1 months ago
Unsupervised Classification of X-Ray Mapping Images of Polished Sections
X-ray mapping images of polished sections are classified using two unsupervised clustering algorithms. The methods applied are the k-means algorithm and an extended spectral fuzzy...
Klaus Baggesen Hilger, Allan Aasbjerg Nielsen, Jen...
PRL
1998
132views more  PRL 1998»
14 years 11 months ago
Unsupervised feature selection using a neuro-fuzzy approach
A neuro-fuzzy methodology is described which involves connectionist minimization of a fuzzy feature evaluation index with unsupervised training. The concept of a ¯exible membersh...
Jayanta Basak, Rajat K. De, Sankar K. Pal
ECCV
2000
Springer
16 years 1 months ago
Unsupervised Learning of Models for Recognition
We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
Markus Weber, Max Welling, Pietro Perona
ICPR
2008
IEEE
16 years 1 months ago
Unsupervised image embedding using nonparametric statistics
Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
Guobiao Mei, Christian R. Shelton