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JUCS
2006
185views more  JUCS 2006»
13 years 10 months ago
The Berlin Brain-Computer Interface: Machine Learning Based Detection of User Specific Brain States
We outline the Berlin Brain-Computer Interface (BBCI), a system which enables us to translate brain signals from movements or movement intentions into control commands. The main co...
Benjamin Blankertz, Guido Dornhege, Steven Lemm, M...
BMCBI
2007
182views more  BMCBI 2007»
13 years 10 months ago
EDISA: extracting biclusters from multiple time-series of gene expression profiles
Background: Cells dynamically adapt their gene expression patterns in response to various stimuli. This response is orchestrated into a number of gene expression modules consistin...
Jochen Supper, Martin Strauch, Dierk Wanke, Klaus ...
IMAGING
2004
13 years 11 months ago
Estimating Illumination Chromaticity via Support Vector Regression
The technique of support vector regression is applied to the problem of estimating the chromaticity of the light illuminating a scene from a color histogram of an image of the sce...
Brian V. Funt, Weihua Xiong
OZCHI
2006
ACM
14 years 4 months ago
Tangible tiles: design and evaluation of a tangible user interface in a collaborative tabletop setup
In this paper we describe a tangible user interface “Tangible Tiles”, which utilizes optically tracked transparent Plexiglass tiles for interaction and display of projected im...
Manuela Waldner, Jörg Hauber, Jürgen Zau...
TSP
2011
151views more  TSP 2011»
13 years 5 months ago
Stochastic Models for Sparse and Piecewise-Smooth Signals
Abstract—We introduce an extended family of continuous-domain stochastic models for sparse, piecewise-smooth signals. These are specified as solutions of stochastic differential...
Michael Unser, Pouya Dehghani Tafti