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» Training of Classifiers Using Virtual Samples Only
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FGR
2004
IEEE
200views Biometrics» more  FGR 2004»
13 years 11 months ago
Using Random Subspace to Combine Multiple Features for Face Recognition
LDA is a popular subspace based face recognition approach. However, it often suffers from the small sample size problem. When dealing with the high dimensional face data, the LDA ...
Xiaogang Wang, Xiaoou Tang
ESANN
2006
13 years 9 months ago
Classification of Boar Sperm Head Images using Learning Vector Quantization
We apply Learning Vector Quantization (LVQ) in automated boar semen quality assessment. The classification of single boar sperm heads into healthy (normal) and non-normal ones is b...
Michael Biehl, Piter Pasma, Marten Pijl, Lidia S&a...
CORR
2011
Springer
147views Education» more  CORR 2011»
13 years 2 months ago
A Generalized Method for Integrating Rule-based Knowledge into Inductive Methods Through Virtual Sample Creation
Hybrid learning methods use theoretical knowledge of a domain and a set of classified examples to develop a method for classification. Methods that use domain knowledge have been ...
Ridwan Al Iqbal
VR
2010
IEEE
174views Virtual Reality» more  VR 2010»
13 years 5 months ago
Breaking the status quo: Improving 3D gesture recognition with spatially convenient input devices
We present a systematic study on the recognition of 3D gestures using spatially convenient input devices. Specifically, we examine the linear acceleration-sensing Nintendo Wii Re...
Michael Hoffman, Paul Varcholik, Joseph J. LaViola...
PRIB
2010
Springer
242views Bioinformatics» more  PRIB 2010»
13 years 6 months ago
Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis
Abstract. Supervised classifiers require manually labeled training samples to classify unlabeled objects. Active Learning (AL) can be used to selectively label only “ambiguous...
Scott Doyle, Anant Madabhushi