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» Input Modeling Using Quantile Statistical Methods
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131
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BMCBI
2006
121views more  BMCBI 2006»
15 years 1 months ago
Splice site identification using probabilistic parameters and SVM classification
Background: Recent advances and automation in DNA sequencing technology has created a vast amount of DNA sequence data. This increasing growth of sequence data demands better and ...
A. K. M. A. Baten, Bill C. H. Chang, Saman K. Halg...
79
Voted
ICIP
2003
IEEE
16 years 2 months ago
Text to visual synthesis with appearance models
This paper presents a new method named text to visual synthesis with appearance models (TEVISAM) for generating videorealistic talking heads. In a first step, the system learns a ...
Javier Melenchón, Fernando De la Torre, Ign...
139
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DKE
2011
251views Education» more  DKE 2011»
14 years 8 months ago
Generating operation specifications from UML class diagrams: A model transformation approach
One of the more tedious and complex tasks during the specification of conceptual schemas (CSs) is modeling the operations that define the system behavior. This paper aims to simpl...
Manoli Albert, Jordi Cabot, Cristina Gómez,...
148
Voted
SPIEVIP
2010
15 years 3 months ago
Automatic scene activity modeling for improving object classification
In video surveillance, automatic methods for scene understanding and activity modeling can exploit the high redundancy of object trajectories observed over a long period of time. ...
Samuel Foucher, Marc Lalonde, Langis Gagnon
124
Voted
JMLR
2006
140views more  JMLR 2006»
15 years 1 months ago
Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error
The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of active learning in line...
Masashi Sugiyama