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» Improving Generalization by Data Categorization
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CVPR
2011
IEEE
14 years 7 months ago
Mining Discriminative Co-occurrence Patterns for Visual Recognition
The co-occurrence pattern, a combination of binary or local features, is more discriminative than individual features and has shown its advantages in object, scene, and action rec...
Junsong Yuan, Ming Yang, Ying Wu
CSCW
2006
ACM
15 years 5 months ago
Improving network efficiency in real-time groupware with general message compression
Groupware communicates by sending messages across the network, and groupware programmers use a variety of formats for these messages, such as XML, plain text, or serialized object...
Carl Gutwin, Christopher Fedak, Mark Watson, Jeff ...
DGO
2003
128views Education» more  DGO 2003»
15 years 1 months ago
A Study on Automatic Ontology Mapping of Categorical Information
Semantic heterogeneity of information is a major barrier of information and system interoperability. Defining ontology of data and mapping ontologies among heterogeneous informati...
Naijun Zhou
CVPR
2007
IEEE
16 years 1 months ago
Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data
A popular approach to problems in image classification is to represent the image as a bag of visual words and then employ a classifier to categorize the image. Unfortunately, a si...
Liu Yang, Rong Jin, Caroline Pantofaru, Rahul Sukt...
75
Voted
ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
16 years 4 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie