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ICIP
2007
IEEE
14 years 9 months ago
MuFeSaC: Learning When to Use Which Feature Detector
Interest point detectors are the starting point in image analysis for depth estimation using epipolar geometry and camera ego-motion estimation. With several detectors defined in ...
Sreenivas R. Sukumar, David L. Page, Hamparsum Boz...
ICCV
2003
IEEE
14 years 9 months ago
Entropy-of-likelihood Feature Selection for Image Correspondence
Feature points for image correspondence are often selected according to subjective criteria (e.g. edge density, nostrils). In this paper, we present a general, non-subjective crit...
Matthew Toews, Tal Arbel
BMCBI
2005
118views more  BMCBI 2005»
13 years 7 months ago
Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes
Background: In the clinical context, samples assayed by microarray are often classified by cell line or tumour type and it is of interest to discover a set of genes that can be us...
Thanyaluk Jirapech-Umpai, J. Stuart Aitken
CORR
2008
Springer
165views Education» more  CORR 2008»
13 years 7 months ago
Feature Selection By KDDA For SVM-Based MultiView Face Recognition
: Applications such as Face Recognition (FR) that deal with high-dimensional data need a mapping technique that introduces representation of low-dimensional features with enhanced ...
Seyyed Majid Valiollahzadeh, Abolghasem Sayadiyan,...
EMNLP
2010
13 years 5 months ago
Improving Gender Classification of Blog Authors
The problem of automatically classifying the gender of a blog author has important applications in many commercial domains. Existing systems mainly use features such as words, wor...
Arjun Mukherjee, Bing Liu