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» Minimax Entropy and Learning by Diffusion
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CVPR
1997
IEEE
13 years 9 months ago
Learning Generic Prior Models for Visual Computation
This paper presents a novel theory for learning generic prior models from a set of observed natural images based on a minimax entropy theory that the authors studied in modeling t...
Song Chun Zhu, David Mumford
NIPS
2001
13 years 6 months ago
The g Factor: Relating Distributions on Features to Distributions on Images
We describe the g-factor which relates probability distributions on image features to distributions on the images themselves. The g-factor depends only on our choice of features a...
James M. Coughlan, Alan L. Yuille
CVPR
2008
IEEE
14 years 7 months ago
A hierarchical and contextual model for aerial image understanding
In this paper we present a novel method for parsing aerial images with a hierarchical and contextual model learned in a statistical framework. We learn hierarchies at the scene an...
Jake Porway, Kristy Wang, Benjamin Yao, Song Chun ...
BMCBI
2008
106views more  BMCBI 2008»
13 years 5 months ago
A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selec
Background: Cell viability is one of the basic properties indicating the physiological state of the cell, thus, it has long been one of the major considerations in biotechnologica...
Ning Wei, Erwin Flaschel, Karl Friehs, Tim W. Natt...
CSB
2004
IEEE
135views Bioinformatics» more  CSB 2004»
13 years 9 months ago
Selection of Patient Samples and Genes for Outcome Prediction
Gene expression profiles with clinical outcome data enable monitoring of disease progression and prediction of patient survival at the molecular level. We present a new computatio...
Huiqing Liu, Jinyan Li, Limsoon Wong