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» Word Importance Discrimination Using Context Information
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CIVR
2008
Springer
227views Image Analysis» more  CIVR 2008»
14 years 11 months ago
A comparison of color features for visual concept classification
Concept classification is important to access visual information on the level of objects and scene types. So far, intensity-based features have been widely used. To increase discr...
Koen E. A. van de Sande, Theo Gevers, Cees G. M. S...
TIT
2008
105views more  TIT 2008»
14 years 8 months ago
State Discrimination With Post-Measurement Information
We introduce a new state discrimination problem in which we are given additional information about the state after the measurement, or more generally, after a quantum memory bound ...
Manuel A. Ballester, Stephanie Wehner, Andreas Win...
ICCV
2009
IEEE
16 years 2 months ago
Quantifying Contextual Information for Object Detection
Context is critical for minimising ambiguity in object de- tection. In this work, a novel context modelling framework is proposed without the need of any prior scene segmen- tat...
Wei-Shi Zheng, Shaogang Gong and Tao Xiang
ICCV
2007
IEEE
15 years 11 months ago
Proximity Distribution Kernels for Geometric Context in Category Recognition
We propose using the proximity distribution of vectorquantized local feature descriptors for object and category recognition. To this end, we introduce a novel "proximity dis...
Haibin Ling, Stefano Soatto
BMCBI
2007
147views more  BMCBI 2007»
14 years 9 months ago
Comparative analysis of long DNA sequences by per element information content using different contexts
Background: Features of a DNA sequence can be found by compressing the sequence under a suitable model; good compression implies low information content. Good DNA compression mode...
Trevor I. Dix, David R. Powell, Lloyd Allison, Jul...