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» Reduced modeling of signal transduction - a modular approach
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ICASSP
2009
IEEE
14 years 2 months ago
Detecting bandlimited audio in broadcast television shows
For TV and radio shows containing narrowband speech, Speech-to-text (STT) accuracy on the narrowband audio can be improved by using an acoustic model trained on acoustically match...
Mark C. Fuhs, Qin Jin, Tanja Schultz

Publication
1851views
15 years 8 months ago
Cerebrovascular Segmentation from TOF Using Stochastic Models
In this paper, we present an automatic statistical approach for extracting 3D blood vessels from time-of-flight (TOF) magnetic resonance angiography (MRA) data. The voxels of the d...
M. Sabry Hassouna, Aly A. Farag, Stephen Hushek, T...
BCBGC
2008
13 years 9 months ago
BMA - Boolean Matrices as Model for Motif Kernels
We introduce the data model BM, which specifies kernels of motifs by means of Boolean matrices. Different from position frequency matrices these only specify which bases can appea...
Jan Schröder, Manfred Schimmler, Heiko Schr&o...
ICASSP
2009
IEEE
14 years 2 months ago
Posterior features applied to speech recognition tasks with user-defined vocabulary
This paper presents a novel approach for those applications where vocabulary is defined by a set of acoustic samples. In this approach, the acoustic samples are used as reference...
Guillermo Aradilla, Hervé Bourlard, Mathew ...
ICASSP
2011
IEEE
12 years 11 months ago
Variational methods for spectral unmixing of hyperspectral images
This paper studies a variational Bayesian unmixing algorithm for hyperspectral images based on the standard linear mixing model. Each pixel of the image is modeled as a linear com...
Olivier Eches, Nicolas Dobigeon, Jean-Yves Tourner...