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» Multiple fuzzy neural networks modeling with sparse data
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IJCNN
2006
IEEE
14 years 2 months ago
Common Subset Selection of Inputs in Multiresponse Regression
— We propose the Multiresponse Sparse Regression algorithm, an input selection method for the purpose of estimating several response variables. It is a forward selection procedur...
Timo Similä, Jarkko Tikka
TNN
2008
178views more  TNN 2008»
13 years 8 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
ICMI
2009
Springer
171views Biometrics» more  ICMI 2009»
14 years 3 months ago
Static vs. dynamic modeling of human nonverbal behavior from multiple cues and modalities
Human nonverbal behavior recognition from multiple cues and modalities has attracted a lot of interest in recent years. Despite the interest, many research questions, including th...
Stavros Petridis, Hatice Gunes, Sebastian Kaltwang...
GRC
2010
IEEE
13 years 9 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
JMLR
2006
104views more  JMLR 2006»
13 years 8 months ago
Learning Image Components for Object Recognition
In order to perform object recognition it is necessary to learn representations of the underlying components of images. Such components correspond to objects, object-parts, or fea...
Michael W. Spratling