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KBS
2008
98views more  KBS 2008»
13 years 7 months ago
Mixed feature selection based on granulation and approximation
Feature subset selection presents a common challenge for the applications where data with tens or hundreds of features are available. Existing feature selection algorithms are mai...
Qinghua Hu, Jinfu Liu, Daren Yu
AAAI
2011
12 years 9 months ago
Size Adaptive Selection of Most Informative Features
In this paper, we propose a novel method to select the most informative subset of features, which has little redundancy and very strong discriminating power. Our proposed approach...
Si Liu, Hairong Liu, Longin Jan Latecki, Shuicheng...
ICPR
2002
IEEE
14 years 10 months ago
Feature Selection for Pose Invariant Face Recognition
One of the major difficulties in face recognition systems is the in-depth pose variation problem. Most face recognition approaches assume that the pose of the face is known. In th...
Berk Gökberk, Ethem Alpaydin, Lale Akarun
ISMB
1993
13 years 10 months ago
Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools
Weintroduce a parallel approach, "DT-SELECT," for selecting features used by inductive learning algorithms to predict protein secondary structure. DT-SELECTis able to ra...
Kevin J. Cherkauer, Jude W. Shavlik
PRL
2006
180views more  PRL 2006»
13 years 9 months ago
MutualBoost learning for selecting Gabor features for face recognition
This paper describes an improved boosting algorithm, the MutualBoost algorithm, and its application in developing a fast and robust Gabor feature based face recognition system. Th...
LinLin Shen, Li Bai