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» On the Complexity of Train Assignment Problems
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ICPR
2006
IEEE
16 years 5 months ago
A Trainable Similarity Measure for Image Classification
In object recognition problems a two-stage system is usually adopted composed of a fast and simple detector and a more complex classifier. This paper studies a design of the secon...
Jana Novovicová, Pavel Paclík, Rober...
ACIVS
2009
Springer
15 years 10 months ago
Image Categorization Using ESFS: A New Embedded Feature Selection Method Based on SFS
Abstract. Feature subset selection is an important subject when training classifiers in Machine Learning (ML) problems. Too many input features in a ML problem may lead to the so-...
Huanzhang Fu, Zhongzhe Xiao, Emmanuel Dellandr&eac...
ICPP
2008
IEEE
15 years 10 months ago
Dynamic Meta-Learning for Failure Prediction in Large-Scale Systems: A Case Study
Despite great efforts on the design of ultra-reliable components, the increase of system size and complexity has outpaced the improvement of component reliability. As a result, fa...
Jiexing Gu, Ziming Zheng, Zhiling Lan, John White,...
AVSS
2006
IEEE
15 years 7 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
EDM
2010
160views Data Mining» more  EDM 2010»
15 years 5 months ago
Using Neural Imaging and Cognitive Modeling to Infer Mental States while Using an Intelligent Tutoring System
Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distr...
Jon M. Fincham, John R. Anderson, Shawn Betts, Jen...