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» Learning the Relative Importance of Features in Image Data
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SDM
2007
SIAM
121views Data Mining» more  SDM 2007»
13 years 10 months ago
Mining Visual and Textual Data for Constructing a Multi-Modal Thesaurus
We propose an unsupervised approach to learn associations between continuous-valued attributes from different modalities. These associations are used to construct a multi-modal t...
Hichem Frigui, Joshua Caudill
TMI
2008
66views more  TMI 2008»
13 years 8 months ago
Feature Normalization via Expectation Maximization and Unsupervised Nonparametric Classification For M-FISH Chromosome Images
Multicolor fluorescence in situ hybridization (M-FISH) techniques provide color karyotyping that allows simultaneous analysis of numerical and structural abnormalities of whole hum...
Hyohoon Choi, Alan C. Bovik, Kenneth R. Castleman
CIVR
2010
Springer
199views Image Analysis» more  CIVR 2010»
14 years 1 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
MMM
2007
Springer
143views Multimedia» more  MMM 2007»
14 years 3 months ago
Semi-supervised Cast Indexing for Feature-Length Films
Abstract. Cast indexing is a very important application for contentbased video browsing and retrieval, since the characters in feature-length films and TV series are always the ma...
Wei Fan, Tao Wang, Jean-Yves Bouguet, Wei Hu, Yimi...
ICCV
2007
IEEE
14 years 10 months ago
People-LDA: Anchoring Topics to People using Face Recognition
Topic models have recently emerged as powerful tools for modeling topical trends in documents. Often the resulting topics are broad and generic, associating large groups of people...
Vidit Jain, Erik G. Learned-Miller, Andrew McCallu...