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» Training of Classifiers Using Virtual Samples Only
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ECCV
2004
Springer
14 years 9 months ago
A Linguistic Feature Vector for the Visual Interpretation of Sign Language
Abstract. This paper presents a novel approach to sign language recognition that provides extremely high classification rates on minimal training data. Key to this approach is a 2 ...
Richard Bowden, David Windridge, Timor Kadir, Andr...
PR
2006
108views more  PR 2006»
13 years 7 months ago
Boosted discriminant projections for nearest neighbor classification
In this paper we introduce a new embedding technique to find the linear projection that best projects labeled data samples into a new space where the performance of a Nearest Neig...
David Masip, Jordi Vitrià
BMCBI
2008
97views more  BMCBI 2008»
13 years 7 months ago
A Population Proportion approach for ranking differentially expressed genes
Background: DNA microarrays are used to investigate differences in gene expression between two or more classes of samples. Most currently used approaches compare mean expression l...
Mugdha Gadgil
TRECVID
2008
13 years 9 months ago
National Institute of Informatics, Japan at TRECVID 2008
This paper reports our experiments for TRECVID 2008 tasks: high level feature extraction, search and contentbased copy detection. For the high level feature extraction task, we use...
Duy-Dinh Le, Xiaomeng Wu, Shin'ichi Satoh, Sheetal...
ICAPR
2005
Springer
14 years 1 months ago
Texture Exemplars for Defect Detection on Random Textures
We present a new approach to detecting defects in random textures which requires only very few defect free samples for unsupervised training. Each product image is divided into ove...
Xianghua Xie, Majid Mirmehdi