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» Robust Classification with Context-Sensitive Features
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ICASSP
2009
IEEE
14 years 2 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...
ICB
2007
Springer
183views Biometrics» more  ICB 2007»
13 years 11 months ago
Robust Point-Based Feature Fingerprint Segmentation Algorithm
Abstract. A critical step in automatic fingerprint recognition is the accurate segmentation of fingerprint images. The objective of fingerprint segmentation is to decide which part...
Chaohong Wu, Sergey Tulyakov, Venu Govindaraju
CSDA
2008
126views more  CSDA 2008»
13 years 7 months ago
A new genetic algorithm in proteomics: Feature selection for SELDI-TOF data
Mass spectrometry from clinical specimens is used in order to identify biomarkers in a diagnosis. Thus, a reliable method for both feature selection and classification is required...
Christelle Reynès, Robert Sabatier, Nicolas...
NIPS
2001
13 years 9 months ago
Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade
This paper develops a new approach for extremely fast detection in domains where the distribution of positive and negative examples is highly skewed (e.g. face detection or databa...
Paul A. Viola, Michael J. Jones
CVPR
2007
IEEE
14 years 9 months ago
Feature Mining for Image Classification
The efficiency and robustness of a vision system is often largely determined by the quality of the image features available to it. In data mining, one typically works with immense...
Piotr Dollár, Zhuowen Tu, Hai Tao, Serge Be...