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BMVC
2010
14 years 9 months ago
Local Gaussian Processes for Pose Recognition from Noisy Inputs
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
Martin Fergie, Aphrodite Galata
BMCBI
2005
122views more  BMCBI 2005»
14 years 11 months ago
FACT - a framework for the functional interpretation of high-throughput experiments
Background: Interpreting the results of high-throughput experiments, such as those obtained from DNA-microarrays, is an often time-consuming task due to the high number of data-po...
Felix Kokocinski, Nicolas Delhomme, Gunnar Wrobel,...
GRC
2010
IEEE
15 years 3 days 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
63
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ICIP
2000
IEEE
16 years 18 days ago
A Fast Hierarchical Algorithm of Maximum Intensity Projection
The maximum intensity projection (MIP) is a useful tool to visualize 3D images. The processing time of the MIP depends on the number of voxels of the 3D data. Therefore, it is ver...
Keun Ho Kim, Min Jeong Kwon, Hyun Wook Park
SETN
2004
Springer
15 years 4 months ago
A Meta-classifier Approach for Medical Diagnosis
Abstract. Single classifiers, such as Neural Networks, Support Vector Machines, Decision Trees and other, can be used to perform classification of data for relatively simple proble...
George L. Tsirogiannis, Dimitrios S. Frossyniotis,...