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BMCBI
2010
190views more  BMCBI 2010»
13 years 4 months ago
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification alg
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...
ECCV
2006
Springer
14 years 6 months ago
Learning to Detect Objects of Many Classes Using Binary Classifiers
Viola and Jones [VJ] demonstrate that cascade classification methods can successfully detect objects belonging to a single class, such as faces. Detecting and identifying objects t...
Ramana Isukapalli, Ahmed M. Elgammal, Russell Grei...
ICPR
2006
IEEE
14 years 5 months ago
Enhancing Training Set for Face Detection
We present a novel method to enhance training set for face detection with nonlinearly generated examples from the original data. The motivation is from Support Vector Machines (SV...
Ruiping Wang, Jie Chen, Shiguang Shan, Wen Gao
ICIP
2007
IEEE
14 years 6 months ago
Color Image Superresolution Based on a Stochastic Combinational Classification-Regression Algorithm
Abstract - The proposed algorithm in this work provides superresolution for color images by using a learning based technique that utilizes both generative and discriminant approach...
Karl S. Ni, Truong Q. Nguyen
CORR
2000
Springer
84views Education» more  CORR 2000»
13 years 4 months ago
Robust Classification for Imprecise Environments
In real-world environments it usually is difficult to specify target operating conditions precisely, for example, target misclassification costs. This uncertainty makes building ro...
Foster J. Provost, Tom Fawcett