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» Extremal Optimization: Methods derived from Co-Evolution
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CVPR
2009
IEEE
15 years 3 months ago
A Min-Max Framework of Cascaded Classifier with Multiple Instance Learning for Computer Aided Diagnosis
The computer aided diagnosis (CAD) problems of detecting potentially diseased structures from medical images are typically distinguished by the following challenging characterist...
Dijia Wu (Rensselaer Polytechnic Institute), Jinbo...
CVPR
2006
IEEE
14 years 10 months ago
Control Theory and Fast Marching Techniques for Brain Connectivity Mapping
We propose a novel, fast and robust technique for the computation of anatomical connectivity in the brain. Our approach exploits the information provided by Diffusion Tensor Magne...
Emmanuel Prados, Stefano Soatto, Christophe Lengle...
BMCBI
2010
151views more  BMCBI 2010»
13 years 8 months ago
Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
Background: Because a priori knowledge about function of G protein-coupled receptors (GPCRs) can provide useful information to pharmaceutical research, the determination of their ...
Zhanchao Li, Xuan Zhou, Zong Dai, Xiaoyong Zou
ECCV
2006
Springer
14 years 10 months ago
Unsupervised Texture Segmentation with Nonparametric Neighborhood Statistics
Abstract. This paper presents a novel approach to unsupervised texture segmentation that relies on a very general nonparametric statistical model of image neighborhoods. The method...
Suyash P. Awate, Tolga Tasdizen, Ross T. Whitaker
ICIP
2000
IEEE
14 years 10 months ago
The Iterative Deconvolution of Linearly Blurred Images Using Non-Parametric Stabilizing Functions
An iterative solution to the problem of image deconvolution is presented. The previous image estimate is pre-filtered using a stabilizing function that is updated based on current...
James R. Hare, James P. Reilly