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» Improved analysis methods for crossover-based algorithms
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126
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MM
2010
ACM
115views Multimedia» more  MM 2010»
15 years 1 months ago
Interactive learning of heterogeneous visual concepts with local features
In the context of computer-assisted plant identification we are facing challenging information retrieval problems because of the very high within-class variability and of the lim...
Wajih Ouertani, Michel Crucianu, Nozha Boujemaa
123
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WWW
2004
ACM
16 years 4 months ago
Query and content suggestion based on latent interest and topic class
To improve the process of user information retrieval, we propose the concept of a latent semantic map (LSM), along with a method of generating this map. The novel aspect of the LS...
Noriaki Kawaeme, Hideaki Suzuki, Osamu Mizuno
159
Voted
JBI
2004
171views Bioinformatics» more  JBI 2004»
15 years 4 months ago
Consensus Clustering and Functional Interpretation of Gene Expression Data
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...
162
Voted
TIP
2002
179views more  TIP 2002»
15 years 3 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
123
Voted
IBPRIA
2003
Springer
15 years 8 months ago
Does Independent Component Analysis Play a~Role in Unmixing Hyperspectral Data?
—Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a li...
José M. P. Nascimento, José M. B. Di...