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» Building an Ontology of Visualization
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CVPR
2008
IEEE
16 years 8 months ago
Margin-based discriminant dimensionality reduction for visual recognition
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
Hakan Cevikalp, Bill Triggs, Frédéri...
IJCV
2008
192views more  IJCV 2008»
15 years 6 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
ICMCS
2005
IEEE
105views Multimedia» more  ICMCS 2005»
16 years 2 days ago
Speech-Based Visual Concept Learning Using Wordnet
Modeling visual concepts using supervised or unsupervised machine learning approaches are becoming increasing important for video semantic indexing, retrieval, and filtering appli...
Xiaodan Song, Ching-Yung Lin, Ming-Ting Sun
WAPCV
2004
Springer
15 years 11 months ago
A Visual Attention-Based Approach for Automatic Landmark Selection and Recognition
Visual attention refers to the ability of a vision system to rapidly detect visually salient locations in a given scene. On the other hand, the selection of robust visual landmarks...
Nabil Ouerhani, Heinz Hügli, Gabriel Gruener,...
INFOVIS
2000
IEEE
15 years 11 months ago
Visualizing Massive Multi-Digraphs
We describe MGV, an integrated visualization and exploration system for massive multi-digraph navigation. MGV’s only assumption is that the vertex set of the underlying digraph ...
James Abello, Jeffrey L. Korn