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DAGM
1998
Springer
14 years 1 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
DICTA
2003
13 years 11 months ago
False-Peaks-Avoiding Mean Shift Method for Unsupervised Peak-Valley Sliding Image Segmentation
The mean shift (MS) algorithm is sensitive to local peaks. In this paper, we show both empirically and analytically that when using sample data, the reconstructed PDF may have fals...
Hanzi Wang, David Suter
CIVR
2010
Springer
199views Image Analysis» more  CIVR 2010»
14 years 2 months ago
Unsupervised multi-feature tag relevance learning for social image retrieval
Interpreting the relevance of a user-contributed tag with respect to the visual content of an image is an emerging problem in social image retrieval. In the literature this proble...
Xirong Li, Cees G. M. Snoek, Marcel Worring
IJPRAI
2008
144views more  IJPRAI 2008»
13 years 9 months ago
Unsupervised Learning of a Hierarchy of Topological Maps Using Omnidirectional Images
unsupervised construction of topological maps, which provide an abstraction of the environment in terms of visual aspects. An unsupervised clustering algorithm is used to represent...
Ales Stimec, Matjaz Jogan, Ales Leonardis
CMIG
2010
110views more  CMIG 2010»
13 years 4 months ago
Unsupervised SVM-based gridding for DNA microarray images
This paper presents a novel method for unsupervised DNA microarray gridding based on Support Vector Machines (SVMs). Each spot is a small region on the microarray surface where cha...
Dimitris G. Bariamis, Dimitris Maroulis, Dimitrios...