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» Neural Model Identification Using Local Robustness Analysis
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BMCBI
2004
158views more  BMCBI 2004»
13 years 7 months ago
A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...
AAAI
2004
13 years 8 months ago
Rapid Object Recognition from Discriminative Regions of Interest
Object recognition and detection represent a relevant component in cognitive computer vision systems, such as in robot vision, intelligent video surveillance systems, or multi-mod...
Gerald Fritz, Christin Seifert, Lucas Paletta, Hor...
BMCBI
2007
179views more  BMCBI 2007»
13 years 7 months ago
Automated smoother for the numerical decoupling of dynamics models
Background: Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a pa...
Marco Vilela, Carlos Cristiano H. Borges, Susana V...
BMCBI
2010
106views more  BMCBI 2010»
13 years 2 months ago
Identification and correction of previously unreported spatial phenomena using raw Illumina BeadArray data
Background: A key stage for all microarray analyses is the extraction of feature-intensities from an image. If this step goes wrong, then subsequent preprocessing and processing s...
Mike L. Smith, Mark J. Dunning, Simon Tavaré...
CSL
2010
Springer
13 years 7 months ago
Monaural speech separation based on MAXVQ and CASA for robust speech recognition
Robustness is one of the most important topics for automatic speech recognition (ASR) in practical applications. Monaural speech separation based on computational auditory scene a...
Peng Li, Yong Guan, Shijin Wang, Bo Xu, Wenju Liu