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» Modeling and analysis of content identification
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DRR
2008
13 years 10 months ago
Whole-book recognition using mutual-entropy-driven model adaptation
We describe an approach to unsupervised high-accuracy recognition of the textual contents of an entire book using fully automatic mutual-entropy-based model adaptation. Given imag...
Pingping Xiu, Henry S. Baird
MIR
2006
ACM
220views Multimedia» more  MIR 2006»
14 years 3 months ago
Robust scene recognition using language models for scene contexts
We propose a robust scene recognition framework using scene context information for multimedia contents. Multimedia contents consist of scene sequences that are more likely to hap...
Ryoichi Ando, Koichi Shinoda, Sadaoki Furui, Takah...
IJCSA
2007
100views more  IJCSA 2007»
13 years 8 months ago
Using Artificial Neural networks for the modelling of a distillation column
The main aim of this paper is to establish a reliable model both for the steady-state and unsteady-state regimes of a nonlinear process. The use of this model should reflect the t...
Yahya Chetouani
CORR
2010
Springer
207views Education» more  CORR 2010»
13 years 9 months ago
Collaborative Hierarchical Sparse Modeling
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Pablo Sprechmann, Ignacio Ramírez, Guillerm...
BMCBI
2007
134views more  BMCBI 2007»
13 years 9 months ago
A framework for significance analysis of gene expression data using dimension reduction methods
Background: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, ide...
Lars Halvor Gidskehaug, Endre Anderssen, Arnar Fla...